{"id":"W2064849217","doi":"10.1063/1.1350441","title":"Molecular, metabolic, and genetic control: An introduction","year":2001,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computational biology; Biology; Control (management); Genetics; Evolutionary biology; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004247065,0.0001326097,0.0001681395,0.00015871,0.000161936,0.00007223335,0.0003700835,0.00005215098,0.00001225887],"category_scores_gemma":[0.00004343858,0.000113812,0.00006069904,0.0001810598,0.0002757568,0.00004501577,0.0001939055,0.0001225006,9.475389e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009884883,"about_ca_system_score_gemma":0.00008145783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001150226,"about_ca_topic_score_gemma":0.00000612463,"domain_scores_codex":[0.9989228,0.00003522442,0.0002925207,0.0002976357,0.000221612,0.0002301828],"domain_scores_gemma":[0.9990702,0.000003692293,0.0001232555,0.000296831,0.0002540743,0.0002519205],"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":[0.0001201771,0.00009337875,0.001016075,0.000004410197,0.00001834422,0.00004779522,0.0002074433,0.005830457,0.9793767,0.00003582234,0.00002861197,0.01322074],"study_design_scores_gemma":[0.003433871,0.008512066,0.1021278,0.00005783142,0.0001875372,0.01619956,0.002121292,0.09174066,0.7578823,0.0006141694,0.01607844,0.001044517],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9409829,0.00117049,0.05677283,0.000581416,0.0003836277,0.0000624305,0.000003045889,0.000005102471,0.00003814372],"genre_scores_gemma":[0.9897894,0.0002228296,0.008619627,0.00007124035,0.001254106,0.000001373638,0.000003451879,0.00001488417,0.00002311566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2214945,"threshold_uncertainty_score":0.464112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007369290467176804,"score_gpt":0.3283676269141815,"score_spread":0.3209983364470047,"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."}}