{"id":"W4416746008","doi":"10.1016/j.geomat.2025.100088","title":"Machine and deep learning methods for satellite-derived bathymetric mapping in Canadian coastal waters","year":2025,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; York University; European Space Agency","keywords":"Bathymetry; Shore; Deep water; Transferability; Deep learning; Waves and shallow water; Range (aeronautics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007651694,0.001098905,0.000304638,0.001750987,0.0006127742,0.000962076,0.00112081,0.000453584,0.0008155528],"category_scores_gemma":[0.002031745,0.0002568854,0.0005354974,0.001603423,0.0003756128,0.000710031,0.0008112036,0.0007434181,0.0003233027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005441272,"about_ca_system_score_gemma":0.006181754,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8309146,"about_ca_topic_score_gemma":0.8138809,"domain_scores_codex":[0.9996723,0.00003986954,0.00001912538,0.00007855119,0.0001168999,0.0000732937],"domain_scores_gemma":[0.9993885,0.0001456361,0.00005047357,0.00003747685,0.000339112,0.00003880235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001005782,0.00007200399,0.03992177,0.0001157295,0.00008952439,0.0001460217,0.0002126128,0.4398503,0.003448808,0.001758417,0.007121159,0.507163],"study_design_scores_gemma":[0.000007419781,0.00001230134,0.009181494,0.00001935725,0.00001376788,0.00001621867,0.0001016704,0.9864187,0.001561601,0.0009638977,0.001687383,0.00001616374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6606205,0.004523081,0.3081583,0.00242181,0.0001898913,0.0001923622,0.005851916,0.006171928,0.01187023],"genre_scores_gemma":[0.9043493,0.000891065,0.08543061,0.0001999207,0.00002547586,0.00005080027,0.004055208,0.00009713036,0.004900458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1690854,"threshold_uncertainty_score":0.3401623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008794699790426271,"score_gpt":0.2694844032116083,"score_spread":0.260689703421182,"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."}}