发表机构
Atlantic International Research Centre (AIR Centre)（大西洋国际研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究地球观测分类器评估问题，指出固定召回率下报告精度有偏差。提出基于平衡测试、业务化先验和实际部署后三个数值的先验匹配报告方法，通过精度优先、泄漏控制开发周期改进分类器，提升精度并能转移判别能力。
AI 中文摘要
内波服务筛选哨兵 - 1波模式存档中的内孤立波，并将检测结果发送给专家，专家裁决时间是需要节省的资源。由于关注错误成本，精度很重要。其分类器在一对一的类别平衡下训练和报告，这在知晓业务化速率之前就已确定。实际业务化速率约为二十分之一，平衡测试分数严重高估了验证者达到的精度。一个平衡测试精度为0.794的模型在实际操作中精度为0.192，这种差距是在错误先验下报告的系统假象。我们表明这种不匹配是一个评估问题，固定召回率下的先验校正和校准无法提高精度，我们提出一种基于三个数值的先验匹配报告方法：平衡测试、业务化先验和实际部署后，它们的对比是真实度量。先精度优先、泄漏控制的开发周期逐步改进分类器，每个改进仅针对预先注册的余量；增加容量未达要求，校准无效，特征聚合是真正提升，因此真实负样本与增益一样是结果。将召回率保持在0.80，针对密封的单读锁箱进行认证，改进后的模型在业务化先验下报告精度为0.927；超时检查确认判别能力可转移到未见时期，而固定操作点则不行。先验匹配报告从平衡开始，然后随着数据流揭示先验而转向先验，可转移到任何业务化地球观测服务，为在尚未发现的先验下引导罕见事件探测器提供支持。
英文摘要
The Internal Waves Service screens the Sentinel-1 Wave-mode archive for internal solitary waves, routing detections to experts whose adjudication time is the resource the effort exists to conserve. Because attention is the cost of error, precision leads. Its classifier was trained and reported at a one-to-one class balance, fixed before the operational rate could be known. That rate has since emerged at roughly one scene in twenty, and a balanced-test score badly overstates the precision a validator meets. A model that scores 0.794 balanced-test precision scores 0.192 in real operation: the gap is a systematic artefact of reporting at the wrong prior, invisible to the metric most work quotes. We show the mismatch to be an evaluation problem in the costume of a training one at a fixed recall, prior correction and calibration cannot move precision, and answer it with a prior-matched reporting method based on three numbers: balanced-test, operational-prior, and real post-deployment, whose contrast is the honest measure. A precision-first, leakage-controlled development cycle then improves the classifier lever by lever, each promoted only against a pre-registered margin; negative variety and the aggregation head lifting, capacity paying once then stopping, calibration inert, so the honest negatives are as much a result as the gains. Holding recall at a floor of 0.80 and certifying against a sealed, single-read lockbox, the promoted model reports 0.927 precision at the operational prior; an out-of-time check confirms discrimination transfers to unseen periods while a fixed operating point does not. Prior-matched reporting, begin balanced, then move to the prior as the stream reveals it, transfers to any operational Earth-observation service bootstrapping a rare-event detector under a prior it has yet to discover.
Comments24 pages, 6 figures, 1 table
