{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000258649,0.0001822383,0.0001905613,0.0005832657,0.00009798769,0.0002565927,0.0001241967,0.0001266778,0.0006721744],"category_scores_gemma":[0.0004627054,0.0001160808,0.0001448066,0.0003426844,0.0001486644,0.0001227538,0.0001583227,0.00008321466,0.0001481574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001225337,"about_ca_system_score_gemma":0.00009143686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002269132,"about_ca_topic_score_gemma":0.003913468,"domain_scores_codex":[0.9998505,0.00002468147,0.00001934127,0.00005124289,0.00003496041,0.00001936299],"domain_scores_gemma":[0.9998542,0.00003431234,0.00005270459,0.00001538749,0.00002756081,0.0000158668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004531209,0.00003928312,0.832642,0.0000476769,0.0001040412,0.0001632984,0.0004986669,0.0002460126,0.1431286,0.0000520886,0.0001105533,0.02251467],"study_design_scores_gemma":[0.000001544881,0.00008762651,0.9967461,0.000002312249,0.00001420332,0.0001895115,0.00006806511,0.0002906579,0.002474025,0.000006466898,0.0001169197,0.000002515859],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993269,0.0001247012,0.0002982448,0.00000327457,8.047133e-7,0.000002388212,0.00008355415,0.000006185756,0.0001538614],"genre_scores_gemma":[0.9986092,0.00007586656,0.0007089245,0.000004985008,0.000001385012,0.000005134507,0.0003067963,0.000002721118,0.0002850285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002269132,"threshold_uncertainty_score":0.004511893,"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."}}