{"id":"W4361276902","doi":"10.5194/essd-2023-83","title":"The COASTℓOOC project dataset","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Oceanography; Sampling (signal processing); Mediterranean sea; Seawater; Environmental science; Mediterranean climate; Channel (broadcasting); Geography; Geology; Computer science; Telecommunications; Archaeology","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":[0.001581187,0.001776156,0.001472042,0.003950545,0.0008702422,0.002242558,0.003445531,0.00240686,0.03661577],"category_scores_gemma":[0.006863073,0.0005550248,0.001588738,0.006008927,0.0004661999,0.001648579,0.002323087,0.002011137,0.05439854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00131516,"about_ca_system_score_gemma":0.002302944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01752636,"about_ca_topic_score_gemma":0.02727142,"domain_scores_codex":[0.9983172,0.0003149637,0.000259214,0.000549777,0.0003718596,0.0001869721],"domain_scores_gemma":[0.997166,0.0008540565,0.0002658297,0.0007036173,0.0007492857,0.0002612735],"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":[0.0001260013,0.00004978999,0.001847767,0.0008895669,0.00007971289,0.00005964625,0.00003630589,0.0008913456,0.0001950716,0.0008397031,0.988396,0.006589055],"study_design_scores_gemma":[0.0002991495,0.00005408383,0.005959295,0.0003326621,0.00006508605,0.0001351877,0.0001515929,0.002111908,0.0004817034,0.001823238,0.9885379,0.00004814193],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000407953,0.0001059927,0.0002080279,0.00009696227,0.00003492979,0.00002832304,0.9979398,0.0005501082,0.0006278941],"genre_scores_gemma":[0.0006098404,0.00005314029,0.0005905242,0.00004172983,0.000007809221,0.0001155663,0.9981963,0.00004336245,0.0003416923],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03661577,"threshold_uncertainty_score":0.1224919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05524603241823915,"score_gpt":0.2625026404525305,"score_spread":0.2072566080342913,"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."}}