{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002675134,0.0007002074,0.0004220295,0.0007623059,0.0002653694,0.0005966952,0.0006682032,0.0007159737,0.002067595],"category_scores_gemma":[0.0006738671,0.000284201,0.0005276831,0.000855046,0.0002809597,0.0006954959,0.0005088676,0.0009517745,0.0008070005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007964199,"about_ca_system_score_gemma":0.0007060294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01816518,"about_ca_topic_score_gemma":0.02435733,"domain_scores_codex":[0.9998535,0.00001959328,0.000008488505,0.00004575776,0.00002891159,0.00004367944],"domain_scores_gemma":[0.9998041,0.00005750531,0.00003039808,0.00002976572,0.00006343284,0.00001492151],"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":[0.0002405221,0.0001515073,0.003908375,0.0001677231,0.0001140066,0.0002159772,0.0001014324,0.4706997,0.03582492,0.00383574,0.009181255,0.4755588],"study_design_scores_gemma":[0.000003393569,0.00001694392,0.0008586058,0.00000970405,0.000007129611,0.00001691619,0.0000156294,0.9922536,0.004346495,0.001399761,0.001067144,0.000004749118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1713468,0.002014149,0.8116145,0.0006466667,0.0001445152,0.00006498515,0.00149228,0.006911876,0.005764285],"genre_scores_gemma":[0.7989265,0.0006670685,0.1877009,0.0002521842,0.00005205827,0.0000591849,0.002677876,0.0002190786,0.009445087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01816518,"threshold_uncertainty_score":0.03611887,"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."}}