{"id":"W6987056743","doi":"","title":"Satellite-Derived Bathymetry Using Machine Learning Methods","year":2025,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bathymetry; Random forest; Generalization; Transferability; Artificial neural network; Hydrography; Supervised learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008411133,0.0007464507,0.0003685635,0.001448804,0.0002591605,0.0008914036,0.0008697829,0.0005160389,0.001741423],"category_scores_gemma":[0.002635379,0.000268125,0.000666199,0.001515622,0.0002934361,0.001064992,0.0007839503,0.0006703847,0.001183985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001009803,"about_ca_system_score_gemma":0.001113651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03446257,"about_ca_topic_score_gemma":0.03030477,"domain_scores_codex":[0.9996681,0.00006777916,0.00002089836,0.0001129404,0.0001001835,0.00003003351],"domain_scores_gemma":[0.9993492,0.0002243348,0.00008078785,0.0001002962,0.0002167538,0.00002868507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000557864,0.00006660134,0.01641092,0.00009853972,0.0001132212,0.00006902287,0.00006045314,0.5933009,0.002792252,0.001611716,0.00349402,0.3819266],"study_design_scores_gemma":[0.000004125352,0.000008619976,0.002155782,0.00001349075,0.000006633134,0.00001368977,0.00001728589,0.9945411,0.0009645145,0.001023311,0.001243351,0.000008229123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1989332,0.001601959,0.777431,0.0008130976,0.0002830795,0.0001486684,0.003228515,0.008150405,0.009410278],"genre_scores_gemma":[0.8056464,0.0005330609,0.1851103,0.0001614092,0.00008628753,0.0000856795,0.00368308,0.0002135951,0.004480233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03446257,"threshold_uncertainty_score":0.06852394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.018776406441607,"score_gpt":0.217483134526578,"score_spread":0.198706728084971,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}