{"id":"W2288210940","doi":"10.1016/j.fsi.2016.03.128","title":"Using rainbow trout cell lines to further study and understand the pathogenesis of the coldwater pathogen, Flavobacterium psychrophilum","year":2016,"lang":"en","type":"article","venue":"Fish & Shellfish Immunology","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; University of Waterloo","funders":"","keywords":"Tracking (education); Rainbow trout; Biology; Computer vision; Artificial intelligence; Position (finance); Transformation (genetics); Ground truth; Computer science; Fish <Actinopterygii>; Fishery","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":[0.0005153408,0.0003801099,0.0002231949,0.0002518177,0.0002681748,0.0004887226,0.0003221891,0.0004379698,0.00130525],"category_scores_gemma":[0.0001671216,0.0001610716,0.0005727248,0.0002359299,0.0003482757,0.0005047739,0.0004073424,0.001095277,0.0005722209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007648538,"about_ca_system_score_gemma":0.0005334693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008062571,"about_ca_topic_score_gemma":0.01887606,"domain_scores_codex":[0.9997869,0.00003151205,0.00002300213,0.00003278147,0.00007829191,0.00004751164],"domain_scores_gemma":[0.9998559,0.00003463558,0.00002864897,0.00002587611,0.00003771867,0.00001732607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004984244,0.00003388802,0.001024186,0.00002769207,0.000005553344,0.00003671689,0.00004987933,0.00009012964,0.9979195,0.0001970737,0.00006245707,0.0005030191],"study_design_scores_gemma":[0.0000399576,0.000737423,0.01135223,0.00001495378,0.00005799255,0.0002777074,0.0002750123,0.002533478,0.9778879,0.0001952433,0.006611857,0.00001634186],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668539,0.001231932,0.02678383,0.0005221667,0.0001420003,0.0001394306,0.001350257,0.0001397344,0.002836693],"genre_scores_gemma":[0.9565568,0.002047851,0.0251947,0.000322929,0.00002570715,0.0002032719,0.003172269,0.00004755636,0.012429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008062571,"threshold_uncertainty_score":0.01603127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486841118717304,"score_gpt":0.2114198575328379,"score_spread":0.1965514463456648,"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."}}