{"id":"W4237621323","doi":"10.1042/bio02403042","title":"Dead computers","year":2002,"lang":"en","type":"article","venue":"The Biochemist","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computer graphics (images)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002035641,0.0001288593,0.00008960846,0.00001872112,0.0001303587,0.00004375526,0.000503084,0.0001153008,0.000132561],"category_scores_gemma":[0.0001196681,0.00008655289,0.00008521503,0.00008735964,0.0003438483,0.000001398492,0.0002030275,0.0001043431,0.0002251484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000010834,"about_ca_system_score_gemma":0.00001862071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007407742,"about_ca_topic_score_gemma":0.00000323897,"domain_scores_codex":[0.9990337,0.00002434027,0.0001795709,0.0001912402,0.0002507383,0.0003203737],"domain_scores_gemma":[0.9992495,0.00001862472,0.00004468397,0.0004822804,0.00006416297,0.0001407925],"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":[0.0000291117,0.0001133517,0.0002895399,0.00005454961,0.0000750628,0.000003006124,0.0001797941,0.000005087293,0.6419742,0.00004630925,0.3214144,0.03581561],"study_design_scores_gemma":[0.0004684805,0.0001763599,0.0003370873,0.00001358268,0.00001182191,0.00002532158,0.0001126534,0.001309169,0.5900497,0.00005706221,0.4072015,0.0002373007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9170034,0.004078242,0.002923289,0.00657927,0.0006637505,0.0004772819,0.00005079063,0.0000686368,0.06815536],"genre_scores_gemma":[0.9908426,0.0006757997,0.0006252737,0.0009383411,0.0004983843,0.00000964249,0.00005931437,0.00001365807,0.00633699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08578706,"threshold_uncertainty_score":0.3529524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087120294987808,"score_gpt":0.2592367912199952,"score_spread":0.2383655882701171,"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."}}