{"id":"W6890262764","doi":"10.34943/224c9b05-851e-49b9-9717-fc05ea8d073f","title":"Saanich Inlet Sill Oxygen Sensor Deployed 2017-11-29","year":2018,"lang":"en","type":"dataset","venue":"Ocean Networks Canada Society","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sill; Inlet; Optode; Hydrology (agriculture); Oxygen; Feature (linguistics); Water quality; Oxygen sensor","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005009078,0.001445465,0.0008204096,0.001856352,0.0007440722,0.000931151,0.001972441,0.0009744104,0.01023856],"category_scores_gemma":[0.001585354,0.0003316126,0.0004984232,0.003026009,0.0004054889,0.0008232978,0.0009901691,0.0009928056,0.01601221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002315767,"about_ca_system_score_gemma":0.003331733,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3136544,"about_ca_topic_score_gemma":0.5309204,"domain_scores_codex":[0.9995164,0.0000403093,0.00002947652,0.0001150507,0.0001910435,0.0001078589],"domain_scores_gemma":[0.9990585,0.00006677542,0.00005132936,0.0001714621,0.000542075,0.000109823],"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":[0.00006731872,0.00002810751,0.003040016,0.0002315009,0.00002412488,0.00004896943,0.00004012832,0.000926954,0.0002648649,0.0004362392,0.991072,0.003819687],"study_design_scores_gemma":[0.0001184333,0.00002469403,0.02045018,0.0002383614,0.00002485564,0.00007924905,0.0003242654,0.003466931,0.001219603,0.001125947,0.9728754,0.0000521219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001466097,0.00008759914,0.0001804895,0.0001126217,0.00005113312,0.00001931435,0.9953956,0.0006693564,0.00201782],"genre_scores_gemma":[0.002006966,0.00005023292,0.0003875753,0.00002520528,0.000006828872,0.00003076504,0.9963607,0.00004079617,0.001090852],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6863456,"threshold_uncertainty_score":0.6236573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01172726148231324,"score_gpt":0.22539356160289,"score_spread":0.2136663001205767,"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."}}