{"id":"W3204616943","doi":"10.1016/j.tibs.2021.09.003","title":"BioID organelle mapping: you are the company you keep","year":2021,"lang":"en","type":"article","venue":"Trends in Biochemical Sciences","topic":"Biotin and Related Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Organelle; Cell fractionation; Consistency (knowledge bases); Computational biology; Computer science; Biology; Artificial intelligence; Cell biology; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002185315,0.0001428285,0.0001456799,0.00004854281,0.0002356756,0.00004150046,0.0003886206,0.0001754532,0.00008995995],"category_scores_gemma":[0.00008418857,0.00008858783,0.00008325336,0.0008576912,0.0007991876,0.000002521303,0.0003032433,0.0001652331,0.00001444101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001119645,"about_ca_system_score_gemma":0.00003774436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001594094,"about_ca_topic_score_gemma":0.00002730544,"domain_scores_codex":[0.9987773,0.00005313701,0.0001903187,0.0004669517,0.0001840611,0.0003281824],"domain_scores_gemma":[0.9995756,0.00001853441,0.00006182223,0.0002408371,0.00004376866,0.00005939487],"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":[0.00001151492,0.0001375967,0.01984903,0.000008881615,0.00004066027,0.00001166443,0.0001973799,0.00001188171,0.9544696,0.0001420537,0.0206448,0.004474889],"study_design_scores_gemma":[0.0003460442,0.00006132088,0.01249732,0.00003233616,0.00001118895,0.00003522642,0.002481216,0.00007543457,0.9220372,0.0001715581,0.06198776,0.0002634191],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968087,0.009904605,0.00001393882,0.008289194,0.0002805108,0.000037571,0.00001141711,0.00001735817,0.01335848],"genre_scores_gemma":[0.9957137,0.0007647207,0.000376266,0.0004506166,0.0001552707,0.00000460822,0.00003031992,0.000006163265,0.002498308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04134295,"threshold_uncertainty_score":0.3612507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02842770207916121,"score_gpt":0.2788595126856535,"score_spread":0.2504318106064923,"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."}}