{"id":"W1551029320","doi":"10.1186/gb-2002-3-11-reports4036","title":"Understanding biology through intelligent systems.","year":2002,"lang":"en","type":"article","venue":"Genome Biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; University of Toronto","funders":"","keywords":"Systems biology; Cognitive science; Computational biology; Computer science; Data science; Biology; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002064929,0.00129051,0.0008612745,0.001765457,0.0008547312,0.00367245,0.001011989,0.001797556,0.01337643],"category_scores_gemma":[0.003015357,0.0006392682,0.000641609,0.001307021,0.003014247,0.005541076,0.001787428,0.002457482,0.003550502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001393011,"about_ca_system_score_gemma":0.001297506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003880528,"about_ca_topic_score_gemma":0.007328632,"domain_scores_codex":[0.9991596,0.000200948,0.0000516715,0.0001382882,0.000386745,0.00006277266],"domain_scores_gemma":[0.9983628,0.0008887089,0.00006861902,0.0002485032,0.0002720265,0.0001592503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007911483,0.0001209685,0.001010331,0.0009400465,0.0001525299,0.0001151281,0.0007474596,0.004777279,0.002272019,0.2615124,0.3762195,0.3520533],"study_design_scores_gemma":[0.00001884866,0.00003383353,0.0009155003,0.0003632341,0.00005176186,0.0001511829,0.0001765958,0.00529296,0.002407375,0.2893688,0.7011949,0.00002494172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.004142538,0.4396872,0.30027,0.07340375,0.01180318,0.0001758329,0.001307795,0.0027703,0.1664393],"genre_scores_gemma":[0.1491693,0.3600618,0.2810943,0.008887268,0.01071123,0.0004317727,0.003402915,0.0007329776,0.1855087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01337643,"threshold_uncertainty_score":0.04474854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1396815901100141,"score_gpt":0.3169006819429507,"score_spread":0.1772190918329366,"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."}}