{"id":"W6889762141","doi":"10.26023/r2ya-c0b9-2n02","title":"C3O - Sir Wilfrid Laurier CTD Data 2014 for DBO5. Version 1.0","year":2016,"lang":"en","type":"dataset","venue":"Earth Observing Laboratory","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"CTD; Profiling (computer programming); Beam (structure); High resolution; Line (geometry)","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":[0.0009300258,0.001923313,0.00127154,0.002694499,0.0007188534,0.001873307,0.003009486,0.001589886,0.04908901],"category_scores_gemma":[0.00426506,0.0007154912,0.001142364,0.005042983,0.0003933953,0.001417863,0.002101059,0.001513312,0.07682654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395662,"about_ca_system_score_gemma":0.002264801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06623821,"about_ca_topic_score_gemma":0.1097932,"domain_scores_codex":[0.9991238,0.0001056022,0.0001024553,0.0002372793,0.0002516049,0.0001793584],"domain_scores_gemma":[0.9982619,0.0002133862,0.0001645773,0.0004884304,0.0006864993,0.0001852173],"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":[0.00004006474,0.00001534337,0.001143456,0.0003004767,0.00002619801,0.00001725842,0.00002616907,0.0003789743,0.0001596196,0.0002817586,0.9956442,0.001966604],"study_design_scores_gemma":[0.0001491385,0.00001050163,0.007943009,0.0002209377,0.00002481151,0.00003548768,0.0001170372,0.0008102569,0.0005734004,0.0008135856,0.9892659,0.00003599891],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001327676,0.00002390245,0.00007439333,0.00003529074,0.00001923589,0.000007253254,0.9987357,0.0004721622,0.0004992711],"genre_scores_gemma":[0.0003346657,0.00001562305,0.0002425403,0.00001412752,0.000004075661,0.00002628276,0.9988926,0.0001061374,0.0003639298],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06623821,"threshold_uncertainty_score":0.1642191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0378699960150568,"score_gpt":0.2828272606313939,"score_spread":0.244957264616337,"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."}}