{"id":"W4385899410","doi":"10.5194/essd-15-3529-2023","title":"The Coastal Surveillance Through Observation of Ocean Color (COASTℓOOC) dataset","year":2023,"lang":"en","type":"article","venue":"Earth system science data","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Oceanography; Sampling (signal processing); Mediterranean sea; Environmental science; Seawater; Coastal sea; Mediterranean climate; Remote sensing; Meteorology; Climatology; Geography; Geology; Computer science","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":[0.001284227,0.001146861,0.00100456,0.002837825,0.0005431284,0.001102257,0.002382713,0.001349275,0.00506088],"category_scores_gemma":[0.003105288,0.000407347,0.0009239396,0.004327541,0.000289397,0.0008073174,0.001860352,0.001068828,0.009028812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024533,"about_ca_system_score_gemma":0.001558659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03964021,"about_ca_topic_score_gemma":0.05743597,"domain_scores_codex":[0.9990721,0.0001424636,0.0001403462,0.0002302943,0.0002931326,0.0001217064],"domain_scores_gemma":[0.9979616,0.0003279778,0.0002839957,0.000510975,0.0006817829,0.0002335914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003350613,0.0002318778,0.0402688,0.001062951,0.0002957634,0.0002791853,0.0001769357,0.003824334,0.002066415,0.0008156303,0.92213,0.02851285],"study_design_scores_gemma":[0.0005823409,0.0001987492,0.2461262,0.000529569,0.000174751,0.0003084886,0.0007960743,0.01449519,0.004363402,0.001326769,0.7308998,0.0001987183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00618983,0.00009064856,0.000345455,0.00008386221,0.00003955839,0.00005489945,0.9919681,0.0004695371,0.0007581255],"genre_scores_gemma":[0.003262045,0.00003157488,0.0009447105,0.00002205624,0.000006637506,0.0001040699,0.9953769,0.00001891679,0.000232986],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03964021,"threshold_uncertainty_score":0.07881898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06279683189249886,"score_gpt":0.262081658280077,"score_spread":0.1992848263875781,"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."}}