{"id":"W4398559595","doi":"10.7910/dvn/ehqzx1","title":"Artificial Intelligence Based Machine Learning Models Predict Sperm parameter Upgrading after Varicocele Repair: A Multi-Institutional Analysis","year":2021,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Sperm and Testicular Function","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Varicocele; Sperm; Computer science; Artificial intelligence; Machine learning; Andrology; Medicine; Biology; Infertility","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004715866,0.0007259556,0.0005577748,0.001648444,0.0004406044,0.0009080881,0.0008639609,0.0005491391,0.001206783],"category_scores_gemma":[0.008103732,0.0002941147,0.001631071,0.0009532061,0.0003976071,0.0005150666,0.0008529522,0.0007780764,0.0002028304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152984,"about_ca_system_score_gemma":0.0007974686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02100966,"about_ca_topic_score_gemma":0.01287214,"domain_scores_codex":[0.9989187,0.0005515584,0.00007449529,0.000229147,0.0001013666,0.000124783],"domain_scores_gemma":[0.9934795,0.00392965,0.001017217,0.000560131,0.0006012786,0.0004122264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004944704,0.0004790417,0.9409742,0.00002834754,0.0008742895,0.0001285388,0.00005491485,0.04776297,0.0002529038,0.00008116052,0.000688365,0.008180706],"study_design_scores_gemma":[0.00005615282,0.00060811,0.4001105,0.00001921101,0.0004749254,0.0002152989,0.0002198754,0.5969907,0.0005172323,0.0003306207,0.0004236219,0.00003363594],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9967632,0.000105419,0.002118238,0.0001288304,0.000008644287,0.0000357715,0.0005820372,0.00004552555,0.0002122301],"genre_scores_gemma":[0.9976701,0.00003961,0.000938957,0.00002174589,0.000007885744,0.00001749686,0.001172613,0.000006205668,0.0001255322],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02100966,"threshold_uncertainty_score":0.04177475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04778644172726596,"score_gpt":0.2668190977119172,"score_spread":0.2190326559846512,"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."}}