{"id":"W4404076354","doi":"10.69649/pachyderm.v30i1.1049","title":"Rhino database workshop","year":2001,"lang":"en","type":"article","venue":"Pachyderm","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cascades (Canada)","funders":"","keywords":"Database; Computer science; Environmental resource management; Geography; Environmental science","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":[0.001893121,0.002507408,0.002636069,0.005053715,0.001011751,0.006384245,0.003621202,0.001636414,0.213892],"category_scores_gemma":[0.005255941,0.001048255,0.001791797,0.004456576,0.0004266467,0.006784905,0.004894557,0.001943188,0.279068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007531318,"about_ca_system_score_gemma":0.001723768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006355836,"about_ca_topic_score_gemma":0.00703599,"domain_scores_codex":[0.9986899,0.0001799599,0.0001696494,0.0002967105,0.0005393925,0.0001243272],"domain_scores_gemma":[0.9979573,0.0003193195,0.00008530218,0.0008857813,0.00045903,0.0002931808],"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":[0.0002532515,0.0000622631,0.0002258816,0.0003926229,0.00004020131,0.0001041171,0.00003690578,0.000319817,0.0009563976,0.003311796,0.918886,0.07541073],"study_design_scores_gemma":[0.00007300894,0.00001919079,0.0004410258,0.0001454871,0.00002931414,0.0001449755,0.00005633274,0.001552579,0.0008566476,0.003643625,0.993004,0.00003377536],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.004532884,0.008569392,0.06086386,0.004970439,0.003378353,0.0006789564,0.5599357,0.1636824,0.1933881],"genre_scores_gemma":[0.007930607,0.003341348,0.02682518,0.001320858,0.0003657739,0.0003209985,0.8410587,0.01875579,0.1000807],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.213892,"threshold_uncertainty_score":0.7155402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03286173481487725,"score_gpt":0.300434118452811,"score_spread":0.2675723836379338,"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."}}