{"id":"W1985137596","doi":"10.1016/s0734-9750(02)00024-1","title":"Applications of DNA and protein microarrays in comparative physiology","year":2002,"lang":"en","type":"article","venue":"Biotechnology Advances","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"DNA microarray; Biology; Computational biology; Gene; Genome; Microarray; Model organism; Microarray analysis techniques; Gene expression; Genetics; Regulation of gene expression; DNA","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":[],"consensus_categories":[],"category_scores_codex":[0.00002986942,0.00007162513,0.0001138713,0.00007980636,0.00002778014,0.000001515441,0.0001119222,0.0001781474,0.00001409693],"category_scores_gemma":[0.00001289363,0.00006667102,0.00001547656,0.0001435993,0.0002728496,0.000003261566,0.00004385408,0.00006522278,0.00000492746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004365917,"about_ca_system_score_gemma":0.000006238324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001904787,"about_ca_topic_score_gemma":0.00001840746,"domain_scores_codex":[0.9994819,0.00002418287,0.0001311932,0.0002391045,0.00002659499,0.00009700392],"domain_scores_gemma":[0.9996753,0.00000500491,0.00008331369,0.0002008955,0.00002054621,0.00001495262],"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":[0.00001453192,0.00004903489,0.0002217127,0.00001218558,0.000004486333,6.883461e-8,0.00003013995,0.000003229226,0.9870503,0.0009717774,0.0001298453,0.0115127],"study_design_scores_gemma":[0.0002017959,0.00007337074,0.000620144,0.000006876017,0.000001340537,0.000001807689,0.0001579292,0.0000185765,0.7781268,0.0005055735,0.2202272,0.00005857508],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842381,0.0120242,0.001781149,0.0006508831,0.00002504867,0.0003308296,0.000007546335,0.00001663218,0.0009256406],"genre_scores_gemma":[0.9964095,0.001722926,0.001422226,0.0000332914,0.00001934366,0.0001737186,0.000008854829,0.000003855482,0.0002062913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2200974,"threshold_uncertainty_score":0.2718765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01265001864632936,"score_gpt":0.2595879734299067,"score_spread":0.2469379547835774,"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."}}