{"id":"W6969382148","doi":"10.5683/sp/nbkuun","title":"LaurelCreek_Water_Chemical_2011","year":2018,"lang":"en","type":"dataset","venue":"Borealis","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Field (mathematics); Hydrology (agriculture); Water quality; Vegetation (pathology)","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":[0.001284317,0.001375871,0.001016676,0.00209448,0.0006703543,0.001541002,0.001905402,0.001175246,0.03341901],"category_scores_gemma":[0.005109612,0.0005582314,0.0008148437,0.004153365,0.0003484184,0.0009285631,0.001527992,0.001062433,0.03702156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001402526,"about_ca_system_score_gemma":0.002365346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03548926,"about_ca_topic_score_gemma":0.07911083,"domain_scores_codex":[0.9992921,0.0001245635,0.00007890212,0.0002547696,0.0001440206,0.000105665],"domain_scores_gemma":[0.9983582,0.0004619888,0.0002416415,0.0003579232,0.0003859667,0.0001942916],"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":[0.0002544804,0.00006307914,0.01046057,0.001324069,0.00009248243,0.00005027592,0.0000787903,0.0006448692,0.000338583,0.0008011212,0.9786564,0.007235412],"study_design_scores_gemma":[0.0002685962,0.00002947628,0.01726208,0.0002669246,0.0000498287,0.00003573936,0.0001236841,0.0004982575,0.0005244404,0.0007858868,0.9801254,0.00002966426],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004317481,0.00004132983,0.0000750853,0.00004734681,0.00001375198,0.000008029785,0.9985844,0.0001648539,0.0006334673],"genre_scores_gemma":[0.001156598,0.00005685185,0.0003680546,0.00004555528,0.000006041967,0.0000702239,0.997395,0.00004692508,0.0008545616],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03548926,"threshold_uncertainty_score":0.1117977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087025279416869,"score_gpt":0.2298002435014193,"score_spread":0.2189299907072506,"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."}}