{"id":"W4231669943","doi":"10.3410/f.1023032.264769","title":"Faculty Opinions recommendation of The functional landscape of mouse gene expression.","year":2004,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Toronto; Genome Canada","keywords":"Functional genomics; Biology; Gene; Gene expression; Computational biology; Function (biology); Regulation of gene expression; Genomics; Genetics; Genome; DNA microarray; Gene expression profiling","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002213614,0.001049417,0.000727507,0.004444937,0.0008639758,0.002877985,0.001667572,0.00210133,0.6419972],"category_scores_gemma":[0.005975694,0.0005396741,0.0009542279,0.00606529,0.0004010189,0.001705256,0.001255193,0.001784536,0.4917074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001381305,"about_ca_system_score_gemma":0.002857821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005812212,"about_ca_topic_score_gemma":0.01317913,"domain_scores_codex":[0.9989576,0.00006031794,0.0000638241,0.0001266269,0.0006852524,0.0001063198],"domain_scores_gemma":[0.9949124,0.000388861,0.0003490688,0.0004542423,0.002601666,0.001293793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004949351,0.0000382613,0.0003753947,0.0002627108,0.000008022973,0.00003566438,0.0000219486,0.00006709557,0.002528732,0.0007987102,0.9388906,0.05692339],"study_design_scores_gemma":[0.00001478318,0.00002174233,0.002157032,0.0001376108,0.000009352723,0.00003846546,0.00001968505,0.00009478357,0.0006709416,0.0007748635,0.9960507,0.00001011147],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.002631025,0.002630463,0.01412349,0.03389195,0.02007347,0.0007438028,0.2977084,0.01884789,0.6093495],"genre_scores_gemma":[0.006057241,0.004770247,0.01559563,0.006853621,0.005807827,0.0005344543,0.1476965,0.00490864,0.807776],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.6419972,"threshold_uncertainty_score":0.5106475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02633717266144814,"score_gpt":0.3196505532805044,"score_spread":0.2933133806190563,"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."}}