{"id":"W2197831191","doi":"10.1093/humrep/dev305","title":"‘How to count sperm properly’: checklist for acceptability of studies based on human semen analysis","year":2015,"lang":"en","type":"article","venue":"Human Reproduction","topic":"Sperm and Testicular Function","field":"Medicine","cited_by":177,"is_retracted":false,"has_abstract":true,"ca_institutions":"Achieve Life Sciences (Canada)","funders":"","keywords":"Semen; Checklist; Semen analysis; Sperm; Andrology; Gynecology; Medicine; Biology; Infertility; Pregnancy; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001022919,0.000148466,0.0004231471,0.000270198,0.0001331528,0.00002388843,0.00005368036,0.00005202537,0.00006005112],"category_scores_gemma":[0.001342701,0.0001175559,0.0001697552,0.0004923366,0.00008615876,0.00006824639,0.000019619,0.0000782534,0.000004620578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002858507,"about_ca_system_score_gemma":0.00004679308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008993706,"about_ca_topic_score_gemma":0.0001083521,"domain_scores_codex":[0.9984798,0.00004589505,0.000289554,0.000653064,0.0003787306,0.0001528959],"domain_scores_gemma":[0.9978855,0.00001843174,0.0001361902,0.0008933682,0.0009645821,0.0001019299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004501564,0.006291666,0.551052,0.003516813,0.005461016,0.00001979916,0.01112913,0.008433701,0.3432895,0.002472196,0.02988609,0.03394648],"study_design_scores_gemma":[0.003936366,0.007012999,0.8161897,0.0001030425,0.004465352,0.00000975171,0.004186857,0.0009757958,0.1429361,0.0006009061,0.01910085,0.0004823354],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950668,0.0001148562,0.0007748326,0.001712671,0.000267976,0.001190053,0.000005524112,0.00008666144,0.00078066],"genre_scores_gemma":[0.9953385,0.000001039211,0.0007544027,0.0000832716,0.000721111,0.0001285589,0.0001036344,0.00001838861,0.002851109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2651376,"threshold_uncertainty_score":0.4793788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1460211807805812,"score_gpt":0.3805897594989751,"score_spread":0.2345685787183939,"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."}}