{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007948656,0.001007275,0.001624294,0.0005757224,0.0005093417,0.0009247508,0.0009152578,0.0008019467,0.00718535],"category_scores_gemma":[0.0009789915,0.0005471167,0.0008022449,0.0004636525,0.0004285362,0.000964986,0.001038433,0.001692534,0.009566125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002861313,"about_ca_system_score_gemma":0.0004270037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003561842,"about_ca_topic_score_gemma":0.0009851565,"domain_scores_codex":[0.998913,0.0002216747,0.00004043277,0.0001708754,0.0005620259,0.000091875],"domain_scores_gemma":[0.9992275,0.0003051841,0.00004338089,0.0001852473,0.000149899,0.00008889278],"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":[0.0001246622,0.0002025346,0.000186415,0.0001231909,0.00003066868,0.00007537904,0.00002440128,0.000204722,0.9783292,0.0003982584,0.002134566,0.01816606],"study_design_scores_gemma":[0.00007043387,0.00075319,0.001841625,0.00001946975,0.00005763554,0.0002343317,0.00005957055,0.005620713,0.9666215,0.001246307,0.02344603,0.00002928911],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3267493,0.005117238,0.6073533,0.002534642,0.00133424,0.003651287,0.005433075,0.012207,0.03561993],"genre_scores_gemma":[0.5316204,0.00506169,0.3780394,0.001957362,0.000371691,0.003901841,0.01182953,0.001011132,0.06620693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00718535,"threshold_uncertainty_score":0.02403736,"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."}}