{"id":"W2145028173","doi":"10.1016/s0167-7799(00)01479-7","title":"Large-scale screening on small scale","year":2000,"lang":"en","type":"article","venue":"Trends in biotechnology","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Muscular Dystrophy Canada","funders":"","keywords":"Scale (ratio); Computational biology; Biology; Geography; Cartography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007725592,0.0001636209,0.0002027821,0.0003723842,0.00007797764,0.00001185223,0.0004043966,0.0005487428,0.02885609],"category_scores_gemma":[0.000005058888,0.0001666311,0.00006848205,0.0007794762,0.00009401023,0.00001922569,0.00006415054,0.0005522651,0.0001088948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005546625,"about_ca_system_score_gemma":0.000004367512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004524157,"about_ca_topic_score_gemma":0.0002334102,"domain_scores_codex":[0.9988421,0.000007212739,0.0002266253,0.0004207799,0.00008376803,0.0004195597],"domain_scores_gemma":[0.9992092,0.00002037631,0.00004495608,0.0006760425,0.000006599008,0.00004278092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004811769,0.0005546262,0.003029465,0.00001476735,0.00001454624,0.00001750379,0.00008921551,0.00002104162,0.04182556,0.02795125,0.001986182,0.9244477],"study_design_scores_gemma":[0.0007926793,0.0001051255,0.00164431,0.00005054837,0.00001166054,0.00003084982,0.0001318226,0.001247911,0.5161265,0.005263027,0.4741916,0.000403953],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6185251,0.00006903869,0.0006429587,0.004698575,0.00001184839,0.00004147086,0.00004885787,0.001121553,0.3748406],"genre_scores_gemma":[0.9703738,0.0001275681,0.01610523,0.0001516179,0.00005005261,0.00007949418,0.00005688202,0.00002840045,0.01302693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9240438,"threshold_uncertainty_score":0.9720317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665487705991494,"score_gpt":0.2712192710485126,"score_spread":0.2545643939885977,"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."}}