{"id":"W2917652621","doi":"10.1111/rda.13420","title":"Dog sperm swimming parameters analysed by computer‐assisted semen analysis of motility reveal major breed differences","year":2019,"lang":"en","type":"article","venue":"Reproduction in Domestic Animals","topic":"Human-Animal Interaction Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Consejo Nacional para Investigaciones Científicas y Tecnológicas; Ministerio de Ciencia Tecnología y Telecomunicaciones; Instituto Tecnológico de Costa Rica; Ministerio de Economía y Competitividad","keywords":"Breed; Semen analysis; Semen; Sperm; Andrology; Motility; Sperm motility; Biology; Animal science; Medicine; Genetics; Infertility; Pregnancy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005130669,0.0002120512,0.0006203962,0.0002956649,0.00005470663,0.000029314,0.0001801138,0.0001073809,0.0001163253],"category_scores_gemma":[0.0002885587,0.0002005422,0.0002223428,0.0007614932,0.0001271739,0.00001208751,0.0001189705,0.0001183246,0.00001410716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005549342,"about_ca_system_score_gemma":0.00002618069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002912334,"about_ca_topic_score_gemma":0.00006216499,"domain_scores_codex":[0.9977593,0.0001764733,0.0006692071,0.000925041,0.000234081,0.0002358377],"domain_scores_gemma":[0.9986496,0.00007229059,0.0003747972,0.0006496898,0.0002011661,0.00005248778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001889033,0.0001847718,0.3628497,0.00005689223,0.001483525,0.000002315354,0.0001835014,0.0005579933,0.6333393,0.000007913388,0.0004159167,0.000729204],"study_design_scores_gemma":[0.0005591813,0.000450532,0.9633573,0.00003268136,0.0005383202,0.00001377833,0.0004309233,0.001150553,0.03289526,0.00001880448,0.0003091102,0.0002435387],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979443,0.000555566,0.0006717952,0.0001048462,0.0002152565,0.0002674047,0.00003189793,0.00001936155,0.0001896006],"genre_scores_gemma":[0.9977686,0.00005595769,0.001151076,0.00002883631,0.00008640145,0.00001796128,0.0000867372,0.00001360469,0.0007908071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6005076,"threshold_uncertainty_score":0.8177874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221592958363282,"score_gpt":0.3371460634770528,"score_spread":0.31493013389342,"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."}}