{"id":"W1993568797","doi":"10.1142/s0219720015500134","title":"Identification of biomarker genes for resistance to a pathogen by a novel method for meta-analysis of single-channel microarray datasets","year":2015,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Mycotoxins in Agriculture and Food","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Microarray analysis techniques; DNA microarray; Microarray; Gene; Biology; Computational biology; Gene chip analysis; Microarray databases; Identification (biology); Data mining; Computer science; Genetics; Gene expression; Botany","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":[0.003131446,0.001285144,0.001822625,0.005194767,0.000422149,0.001652054,0.001094128,0.0007211874,0.0005031756],"category_scores_gemma":[0.003664959,0.0006034295,0.00317137,0.003486085,0.0003669117,0.0008274067,0.0008815217,0.001291202,0.000247578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000646609,"about_ca_system_score_gemma":0.001000053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001065387,"about_ca_topic_score_gemma":0.001825278,"domain_scores_codex":[0.9981323,0.0004229145,0.0001558477,0.0006635571,0.0005429082,0.00008245957],"domain_scores_gemma":[0.9982207,0.0009164499,0.0002611082,0.0002696905,0.0002663755,0.00006558394],"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":[0.0009478079,0.0008785876,0.03618273,0.001878365,0.007063755,0.0004331509,0.0003925104,0.05294608,0.650302,0.002657506,0.001579658,0.244738],"study_design_scores_gemma":[0.0001625845,0.0007992997,0.04682253,0.00008353359,0.002332482,0.0007473564,0.000298616,0.79743,0.1305301,0.01217677,0.008355129,0.0002616355],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05381427,0.0007757358,0.9401076,0.0001535555,0.00005182179,0.0002771622,0.002336841,0.002147328,0.0003356805],"genre_scores_gemma":[0.1882917,0.0003247574,0.806725,0.00009352221,0.0000436134,0.0007218065,0.003337095,0.0001556626,0.0003069002],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005194767,"threshold_uncertainty_score":0.01656091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0949890221889506,"score_gpt":0.3118014570270975,"score_spread":0.2168124348381469,"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."}}