{"id":"W2519233949","doi":"10.3389/conf.fvets.2016.02.00045","title":"Development of a Sea Lice Surveillance Ontology for Data Integration from Wild Salmon Monitoring Programs on the West Coast of Canada","year":2016,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fishery; Geography; Ontology; Biology; Zoology","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":[0.003680752,0.001172386,0.001099227,0.008434338,0.002812435,0.004504241,0.002347709,0.00129185,0.003124318],"category_scores_gemma":[0.007141599,0.001251254,0.003271943,0.00544194,0.001086273,0.004002059,0.004431499,0.002440365,0.001795136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008705901,"about_ca_system_score_gemma":0.02245081,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6088526,"about_ca_topic_score_gemma":0.6857356,"domain_scores_codex":[0.9972956,0.0001599099,0.0005636635,0.000605991,0.001138084,0.0002367875],"domain_scores_gemma":[0.9949916,0.000747284,0.0003972298,0.0006424744,0.002784752,0.0004366629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003842315,0.0008768025,0.08917391,0.00566349,0.001139451,0.003885298,0.01288953,0.02657782,0.04825988,0.08877367,0.2493683,0.4730075],"study_design_scores_gemma":[0.00006091772,0.00008563887,0.05201587,0.002045842,0.0005569379,0.001049065,0.004045608,0.07999748,0.01887468,0.01749714,0.8234453,0.0003255289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03666888,0.001142389,0.7185324,0.003455591,0.0003941374,0.003340829,0.1480732,0.06201324,0.02637937],"genre_scores_gemma":[0.07759888,0.001637235,0.632022,0.00113377,0.00006005227,0.001294118,0.2682076,0.005331251,0.01271511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3911474,"threshold_uncertainty_score":0.786902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06782982285821826,"score_gpt":0.2965258489166874,"score_spread":0.2286960260584692,"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."}}