{"id":"W3154079029","doi":"10.1117/12.2586977","title":"Deep learning for low altitude coastline segmentation","year":2021,"lang":"en","type":"article","venue":"","topic":"Coastal and Marine Dynamics","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Low altitude; Computer science; Segmentation; Artificial intelligence; Deep learning; Altitude (triangle); Geology; Remote sensing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005641055,0.00004518021,0.00005449348,0.00001374235,0.00007747591,0.00003246905,0.00003280013,0.00001663273,0.001900928],"category_scores_gemma":[0.00003333695,0.00003827589,0.00002884576,0.00006688904,0.0000089088,0.00007540468,0.000009507398,0.00003980964,0.00006982559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001406813,"about_ca_system_score_gemma":0.00002170738,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004974449,"about_ca_topic_score_gemma":0.03347085,"domain_scores_codex":[0.9996243,0.00001249855,0.00007648086,0.0001082009,0.0000666128,0.000111878],"domain_scores_gemma":[0.9997969,0.00006308688,0.0000181131,0.00004024508,0.00004052547,0.00004110795],"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":[0.0000244756,0.0000168618,0.1999324,0.00003062835,0.00001250521,0.000008550966,0.0000763083,0.05696521,0.0004091133,0.0002359035,0.0001880587,0.7421],"study_design_scores_gemma":[0.0003959007,0.0000874256,0.111585,0.000004233048,0.000009997338,0.00001133894,0.0004502145,0.8746458,0.0004352563,0.0006137764,0.01164581,0.0001151746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5668485,0.0002556589,0.400028,0.00092065,0.0006151798,0.0002743602,0.00002908358,0.0001366686,0.03089188],"genre_scores_gemma":[0.9661541,0.00005060118,0.01467613,0.0003577608,0.0000943269,0.000001406806,0.001524644,0.000002316299,0.0171387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8176807,"threshold_uncertainty_score":0.9990115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008915612974018963,"score_gpt":0.2187951522939937,"score_spread":0.2098795393199748,"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."}}