{"id":"W2124797193","doi":"10.1186/1479-5876-7-55","title":"The chemiluminescence based Ziplex® automated workstation focus array reproduces ovarian cancer Affymetrix GeneChip® expression profiles","year":2009,"lang":"en","type":"article","venue":"Journal of Translational Medicine","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University Health Centre; Centre Hospitalier de l’Université de Montréal; McGill University; McGill Genome Centre","funders":"Partenariat Canadien Contre Le Cancer; Canadian Institutes of Health Research; Genome Canada; McGill University Health Centre; Terry Fox Research Institute; Génome Québec; McGill University","keywords":"Gene chip analysis; Chemiluminescence; Ovarian cancer; Microarray; Focus (optics); Computational biology; Cancer; Computer science; Gene expression; Bioinformatics; Gene; Biology; Genetics; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000376819,0.0001098473,0.0001303783,0.00005607131,0.0001600671,0.00001130232,0.0001618095,0.00007777233,0.000008033044],"category_scores_gemma":[0.0001750973,0.00006702096,0.00006084012,0.0002007177,0.00009459903,0.000009616917,0.000003722819,0.0001195269,2.033753e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001305291,"about_ca_system_score_gemma":0.0001020071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003291298,"about_ca_topic_score_gemma":0.000004001257,"domain_scores_codex":[0.9990087,0.00003557064,0.0003901525,0.0001678948,0.0002761611,0.000121585],"domain_scores_gemma":[0.9990326,0.00005470309,0.0003420292,0.0001912045,0.0003191914,0.00006029846],"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":[0.0001607524,0.00003412996,0.0001847951,0.000003943556,0.00001119989,0.000001032167,0.00002424969,0.0003671895,0.9741763,0.00007617479,0.002770763,0.02218951],"study_design_scores_gemma":[0.0006563927,0.000264938,0.00790934,0.0001965454,0.00002973111,0.00002390761,0.00002534234,0.0006996318,0.9768649,0.001398948,0.01182979,0.0001005841],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2610342,0.01266775,0.5896411,0.1347579,0.0004662274,0.0008138288,0.0000342455,0.0001341989,0.0004505646],"genre_scores_gemma":[0.9575441,0.0004300203,0.04094853,0.0002595337,0.0007185176,0.000007361224,0.00003815337,0.000008735383,0.00004498047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.69651,"threshold_uncertainty_score":0.2733035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01441416885815366,"score_gpt":0.3220942505996447,"score_spread":0.3076800817414911,"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."}}