{"id":"W1587332563","doi":"10.1016/s0076-6879(06)10010-5","title":"[10] Optimizing Experiment and Analysis Parameters for Spotted Microarrays","year":2006,"lang":"en","type":"review","venue":"Methods in enzymology on CD-ROM/Methods in enzymology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Zoo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Flagging; Replication (statistics); Computer science; Robustness (evolution); Confidence interval; Data mining; Statistics; Mathematics; Biology; Gene; Genetics; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003060994,0.00352705,0.003405968,0.002403211,0.0004572495,0.001150647,0.005714007,0.00242146,0.005448161],"category_scores_gemma":[0.002402242,0.001781145,0.0009809574,0.003855878,0.001197395,0.002297289,0.001247762,0.003116725,0.009045711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008556862,"about_ca_system_score_gemma":0.00103251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007861014,"about_ca_topic_score_gemma":0.001570057,"domain_scores_codex":[0.9973506,0.000334237,0.0001343754,0.0006040145,0.001465528,0.0001113614],"domain_scores_gemma":[0.9982589,0.000588746,0.0001417547,0.0003060807,0.0006717762,0.00003279712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001612934,0.0001580294,0.0002773357,0.005628393,0.0001155818,0.0001131265,0.00006679298,0.001483587,0.2615536,0.003893677,0.02432347,0.7022251],"study_design_scores_gemma":[0.00007383021,0.0001949132,0.001904887,0.0004651822,0.0002351707,0.002024102,0.00005024294,0.01026277,0.63125,0.005655342,0.3477175,0.0001661302],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003664635,0.1312197,0.8443691,0.001067867,0.001243099,0.0004909579,0.00115401,0.009925868,0.006864749],"genre_scores_gemma":[0.01491229,0.1331509,0.8222106,0.001695681,0.0007803244,0.0009564847,0.003955459,0.001732159,0.02060614],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005714007,"threshold_uncertainty_score":0.01822591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09257389948004525,"score_gpt":0.4650668948132456,"score_spread":0.3724929953332004,"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."}}