{"id":"W7070992157","doi":"","title":"Season Two - Episode Three - Bayani Trinidad and Forrest Eaglespeaker","year":2019,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indigenous; Work (physics)","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":[0.0008787907,0.0004263505,0.00029421,0.000564778,0.00787234,0.003384716,0.001184973,0.002209222,0.1205851],"category_scores_gemma":[0.001939385,0.0003182665,0.0002897258,0.0007733521,0.0009219974,0.001461037,0.004378895,0.003779521,0.02402014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006031072,"about_ca_system_score_gemma":0.007638674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.349075,"about_ca_topic_score_gemma":0.7041408,"domain_scores_codex":[0.9994018,0.00005751046,0.0000122697,0.00007207088,0.0001760715,0.000280226],"domain_scores_gemma":[0.9977688,0.00009237554,0.00004729045,0.0001001041,0.0005966008,0.001394793],"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":[0.0000883063,0.00004261914,0.002044415,0.00006106115,0.000004021436,0.0008591099,0.002665486,0.0000428349,0.0003523528,0.002522425,0.9776184,0.013699],"study_design_scores_gemma":[0.000008202132,0.00001728384,0.004373426,0.00006200634,0.000001433415,0.0001606129,0.00515851,0.00003698266,0.0001145207,0.0003044109,0.9897528,0.00000976426],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04567781,0.001963035,0.001412429,0.06117284,0.01779938,0.0004804239,0.01544189,0.001235731,0.8548164],"genre_scores_gemma":[0.05154245,0.0004795479,0.0006647655,0.009277844,0.00062435,0.0001220058,0.005270924,0.000470916,0.9315472],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.349075,"threshold_uncertainty_score":0.6940863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004359523016685494,"score_gpt":0.1991623353903133,"score_spread":0.1948028123736278,"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."}}