{"id":"W4313280119","doi":"10.1038/s41598-022-25104-6","title":"Machine learning and hypothesis driven optimization of bull semen cryopreservation media","year":2022,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Sperm and Testicular Function","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Extender; Cryopreservation; Machine learning; Cryoprotectant; Artificial intelligence; Semen cryopreservation; Semen; Computer science; Sperm; Sperm motility; Biology; Chemistry; Anatomy; Botany","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":[0.00199764,0.0008363394,0.0006682579,0.0006714131,0.0002460946,0.0007698554,0.0008080281,0.0006797934,0.0007616534],"category_scores_gemma":[0.003088688,0.0003610549,0.0008117414,0.0003560077,0.0004594342,0.0005312713,0.0004656847,0.0008429298,0.000159856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000843444,"about_ca_system_score_gemma":0.0009848722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003226493,"about_ca_topic_score_gemma":0.002869288,"domain_scores_codex":[0.9995951,0.0001552304,0.00002810113,0.0001002259,0.00007631412,0.0000450149],"domain_scores_gemma":[0.9984922,0.001048312,0.0001629259,0.00006268978,0.000204033,0.00002975835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001234068,0.0001416824,0.004842676,0.0001105538,0.0001059428,0.00005473465,0.00003780527,0.9396027,0.005778709,0.0009369815,0.0003226117,0.0479423],"study_design_scores_gemma":[0.000005963254,0.00008119718,0.0006449261,0.000005871592,0.00001355083,0.000006736913,0.000007812683,0.9961629,0.002564079,0.0003508351,0.0001513332,0.000004780358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6086922,0.00176973,0.3845496,0.0005824341,0.00007004847,0.0001431418,0.000459102,0.0009447146,0.002789122],"genre_scores_gemma":[0.9061913,0.0003377352,0.09119517,0.0001161192,0.00002282243,0.0001491022,0.0005745856,0.00005116392,0.00136215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003226493,"threshold_uncertainty_score":0.01056463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01896084275053521,"score_gpt":0.2283964442987649,"score_spread":0.2094356015482297,"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."}}