{"id":"W4394045882","doi":"10.5281/zenodo.8008077","title":"CFdb: interactomes","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Computational biology; Biology","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":[0.0007483913,0.003955856,0.002111951,0.005749764,0.001315855,0.003032946,0.003138526,0.002871574,0.07555489],"category_scores_gemma":[0.003234674,0.001184636,0.002217045,0.007497593,0.00045393,0.00184111,0.003375627,0.002737968,0.08677696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001697182,"about_ca_system_score_gemma":0.00208445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01029493,"about_ca_topic_score_gemma":0.02213689,"domain_scores_codex":[0.999083,0.0001075669,0.00009720489,0.0003268402,0.0002247988,0.0001606396],"domain_scores_gemma":[0.9990593,0.0002756681,0.0001068307,0.0002520262,0.0001507102,0.000155535],"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":[0.0003331743,0.00005566515,0.00247903,0.003426449,0.0002023593,0.0002127221,0.00009643747,0.0009945143,0.002067978,0.001828192,0.9828461,0.005457415],"study_design_scores_gemma":[0.0003190529,0.00003475603,0.005558648,0.0004703408,0.0001001654,0.0003089941,0.00009296372,0.001210988,0.001554048,0.002270873,0.9880266,0.00005250417],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002528432,0.0001350952,0.0001626553,0.00003440628,0.00001245538,0.00001031517,0.9976565,0.001134746,0.0006010028],"genre_scores_gemma":[0.0004597046,0.00008560298,0.0004000744,0.00003192128,0.000002163822,0.00004855675,0.9985535,0.0001434453,0.000275141],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07555489,"threshold_uncertainty_score":0.2527563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02165345386311477,"score_gpt":0.2524756279963016,"score_spread":0.2308221741331869,"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."}}