{"id":"W2169600668","doi":"10.1261/rna.7119904","title":"Probing microRNAs with microarrays: Tissue specificity and functional inference","year":2004,"lang":"en","type":"article","venue":"RNA","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":376,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Biology; microRNA; Gene silencing; DNA microarray; Computational biology; Gene expression; Gene; Regulation of gene expression; Genetics; Microarray; Messenger RNA; Gene expression profiling","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":[0.00174315,0.0008874189,0.001152516,0.0008654984,0.0003685645,0.001021367,0.001021835,0.001177581,0.001309041],"category_scores_gemma":[0.00204231,0.001041323,0.0006689085,0.0007632265,0.0004842131,0.0008582252,0.0005435635,0.001361975,0.002126253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003843639,"about_ca_system_score_gemma":0.0002483302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002589508,"about_ca_topic_score_gemma":0.0007322695,"domain_scores_codex":[0.9981393,0.0005557354,0.00009138585,0.0006338828,0.0004641439,0.0001155876],"domain_scores_gemma":[0.9993535,0.0003718033,0.00007484481,0.0000808912,0.00009347602,0.00002550496],"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":[0.00005741953,0.00002088944,0.0003458496,0.0001102982,0.00002141927,0.00002186978,0.00001743894,0.0003329829,0.9884734,0.000559908,0.0002344712,0.009804133],"study_design_scores_gemma":[0.0000245609,0.0001440657,0.002787225,0.00001911007,0.00007183804,0.0003986991,0.00003824897,0.01628261,0.9663411,0.002327783,0.01152635,0.00003844865],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08689952,0.005135822,0.8960724,0.000486022,0.0002102859,0.00044145,0.002085129,0.003037009,0.005632303],"genre_scores_gemma":[0.146123,0.004796494,0.8397262,0.0006421579,0.0001292001,0.001543994,0.002956833,0.0002782429,0.003803835],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00174315,"threshold_uncertainty_score":0.009218812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01175966002628349,"score_gpt":0.2283780917451022,"score_spread":0.2166184317188187,"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."}}