{"id":"W3037253559","doi":"10.1093/bioinformatics/btaa580","title":"ProbeRating: a recommender system to infer binding profiles for nucleic acid-binding proteins","year":2020,"lang":"en","type":"article","venue":"Bioinformatics","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Nucleic acid; Computer science; Recommender system; Computational biology; DNA-binding protein; Chemistry; Biochemistry; World Wide Web; Biology; Transcription factor; Gene","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":[0.0008220804,0.001413203,0.001032495,0.001572396,0.0004282545,0.0005700486,0.001449775,0.001798955,0.003403332],"category_scores_gemma":[0.003590571,0.0004418317,0.0009100349,0.001106622,0.0002330514,0.001285272,0.0006173951,0.00118602,0.00197333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007610219,"about_ca_system_score_gemma":0.000940075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01560358,"about_ca_topic_score_gemma":0.02791381,"domain_scores_codex":[0.9993293,0.0001415957,0.00004667739,0.000295636,0.0001330673,0.00005365075],"domain_scores_gemma":[0.9985367,0.0008916077,0.0001099564,0.0001515121,0.0002313167,0.00007890491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001762208,0.00107656,0.04506357,0.001537315,0.0008992652,0.0008058962,0.0003541582,0.2030876,0.03913369,0.0036201,0.08477074,0.6178889],"study_design_scores_gemma":[0.00005175808,0.0001977803,0.002663507,0.00003112094,0.00007674469,0.0001854532,0.00004697416,0.9829437,0.005295657,0.002320984,0.006142961,0.00004339587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2535007,0.009098378,0.6685888,0.002409772,0.0005904904,0.0005302281,0.0266,0.0316955,0.006986208],"genre_scores_gemma":[0.5583104,0.002003603,0.3860814,0.001803514,0.0003076929,0.000394674,0.04165978,0.0004892367,0.008949688],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01560358,"threshold_uncertainty_score":0.03102547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03362828354552438,"score_gpt":0.2824179649258074,"score_spread":0.248789681380283,"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."}}