{"id":"W1989373988","doi":"10.1016/j.clinbiochem.2005.04.010","title":"Quality assessment of microarray experiments","year":2005,"lang":"en","type":"article","venue":"Clinical Biochemistry","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Robarts Clinical Trials","funders":"London Health Sciences Centre; Heart and Stroke Foundation of Canada; Agilent Technologies","keywords":"Microarray; Microarray analysis techniques; Concordance; Quality assurance; DNA microarray; Computational biology; Gene expression profiling; Outlier; Biology; Data mining; Bioinformatics; Gene expression; Computer science; Gene; Medicine; Genetics; Mathematics; Statistics; External quality assessment; Pathology","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":[0.06995524,0.001969297,0.003148865,0.006513168,0.002293829,0.004876466,0.002808174,0.001979204,0.005238809],"category_scores_gemma":[0.1537497,0.00142787,0.002566264,0.006385552,0.002789326,0.001857938,0.002918134,0.001986658,0.001530636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002561459,"about_ca_system_score_gemma":0.00255551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002428621,"about_ca_topic_score_gemma":0.004210956,"domain_scores_codex":[0.9131489,0.02859135,0.01270946,0.01133075,0.03197059,0.002248849],"domain_scores_gemma":[0.7842953,0.1089623,0.01163801,0.03754354,0.05623056,0.001330222],"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":[0.00393801,0.00055433,0.08724535,0.006992792,0.003390242,0.0006779951,0.002625332,0.01474459,0.558522,0.0119192,0.01264357,0.2967466],"study_design_scores_gemma":[0.0005482653,0.001102811,0.2214135,0.0007228045,0.003317573,0.002036099,0.0007777936,0.130355,0.5491537,0.01940783,0.07067306,0.0004916062],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09812988,0.004670185,0.8787861,0.001026821,0.0009353401,0.001971984,0.005282138,0.005141151,0.004056308],"genre_scores_gemma":[0.3231336,0.001346001,0.6441514,0.001600721,0.0004093924,0.004518067,0.01774452,0.002830056,0.004266209],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06995524,"threshold_uncertainty_score":0.3699631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08021321054978531,"score_gpt":0.4624209939414959,"score_spread":0.3822077833917106,"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."}}