{"id":"W4393881506","doi":"10.5281/zenodo.5146062","title":"Data and Weights for Reverse Homology","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Homology (biology); Computational biology; Computer science; Biology; Combinatorics; Mathematics; Evolutionary biology; Genetics; Gene","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":[0.001505782,0.002420626,0.000890233,0.002042868,0.0008090016,0.001355711,0.003186889,0.002271313,0.06634359],"category_scores_gemma":[0.01118885,0.000770088,0.001815086,0.002761046,0.0005204478,0.001966881,0.001724408,0.003471705,0.0791089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009320723,"about_ca_system_score_gemma":0.001358512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003462502,"about_ca_topic_score_gemma":0.005882075,"domain_scores_codex":[0.9980686,0.0002253721,0.0002285486,0.000690377,0.0005750514,0.0002120452],"domain_scores_gemma":[0.9965334,0.0006873744,0.0001421291,0.001605535,0.000876026,0.0001555753],"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":[0.0007457926,0.0007591666,0.00595583,0.001103878,0.00009851854,0.0001435648,0.0000799597,0.00540311,0.006437985,0.004525627,0.9130118,0.06173473],"study_design_scores_gemma":[0.0005836086,0.0003706226,0.009707068,0.0002543565,0.00009666112,0.0006356811,0.000204253,0.05115445,0.03298812,0.01603037,0.8878554,0.0001193671],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01280208,0.0003910901,0.01683093,0.0005751636,0.0005813282,0.0005309627,0.9268005,0.02903626,0.01245162],"genre_scores_gemma":[0.013395,0.0001473494,0.02405466,0.0003425306,0.00003719348,0.000955191,0.9538139,0.002194406,0.00505982],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06634359,"threshold_uncertainty_score":0.2219414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06210336118460656,"score_gpt":0.2755117899311676,"score_spread":0.2134084287465611,"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."}}