{"id":"W3143886733","doi":"","title":"1 - Segmentation bathymétrique d'images multispectrales SPOT","year":2001,"lang":"fr","type":"article","venue":"Traitement du signal","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bathymetry; Segmentation; Inversion (geology); Computer science; Context (archaeology); Hydrography; Artificial intelligence; Scale (ratio); Pattern recognition (psychology); Image segmentation; Bathymetric chart; Markov process; Data mining; Geography; Geology; Cartography; Mathematics; Statistics; Geomorphology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0002463911,0.0002744314,0.0002548351,0.0008363724,0.0001919767,0.0006166371,0.0001927954,0.0002785767,0.0019449],"category_scores_gemma":[0.0004669373,0.000168374,0.0002548912,0.0004255654,0.0003309598,0.0004177072,0.0002850159,0.0001962111,0.0006621485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000389905,"about_ca_system_score_gemma":0.0005789249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006791965,"about_ca_topic_score_gemma":0.006764789,"domain_scores_codex":[0.9997497,0.00002745687,0.000009732789,0.00006802165,0.0001101368,0.00003490405],"domain_scores_gemma":[0.999837,0.00003777195,0.00002282423,0.00002732818,0.00006654368,0.000008551303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002207846,0.00007044273,0.01697132,0.0001925691,0.00004752278,0.0002217075,0.0003480545,0.1134132,0.3470718,0.01130662,0.002241303,0.5078947],"study_design_scores_gemma":[0.00001603356,0.00006998496,0.067083,0.00002477193,0.00002425282,0.0005031931,0.0001663409,0.7655022,0.1482938,0.006108638,0.01216034,0.00004754175],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1941701,0.0001827101,0.8006259,0.00009818474,0.00002301852,0.00006516394,0.0005337222,0.001379946,0.002921354],"genre_scores_gemma":[0.7012857,0.0001990823,0.2926183,0.00003389598,0.00001789645,0.00006218997,0.0009133783,0.0002383872,0.004631198],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006791965,"threshold_uncertainty_score":0.01350486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02130206374014152,"score_gpt":0.2441967923764939,"score_spread":0.2228947286363523,"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."}}