{"id":"W2949697368","doi":"","title":"동결정액 인공수정 모돈의 번식성적","year":2018,"lang":"ko","type":"article","venue":"동물자원연구","topic":"Agriculture, Soil, Plant Science","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Semen; Artificial insemination; Animal science; Significant difference; Insemination; Biology; Agricultural science; Medicine; Sperm; Pregnancy; Internal medicine","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":[0.0003676642,0.0001217723,0.0001418557,0.0003202168,0.0004367493,0.0007830235,0.0002774307,0.0001975731,0.004361895],"category_scores_gemma":[0.0006539252,0.00006755745,0.0001859009,0.0003874407,0.0001792803,0.0002293138,0.0001590855,0.0001899241,0.001782268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004422744,"about_ca_system_score_gemma":0.0006823979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01338297,"about_ca_topic_score_gemma":0.01473409,"domain_scores_codex":[0.9997359,0.0000348707,0.00001661111,0.00007427548,0.00009108854,0.00004738328],"domain_scores_gemma":[0.9996032,0.00004624169,0.0001188524,0.00002836669,0.0001627245,0.00004064006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00068826,0.0003366565,0.6425313,0.000293316,0.0001515915,0.001303129,0.001729446,0.0008358783,0.06957593,0.001561707,0.004061637,0.2769312],"study_design_scores_gemma":[0.000008655885,0.001144956,0.9540386,0.00006930353,0.00007337056,0.001533586,0.001225163,0.001046877,0.01216064,0.0004492173,0.02821342,0.00003617142],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784682,0.001425181,0.001663779,0.0002899727,0.00005832756,0.00004195651,0.0006522492,0.00002821979,0.01737207],"genre_scores_gemma":[0.977755,0.001265122,0.001962347,0.0002162325,0.00005723484,0.00003963166,0.00142518,0.00001155552,0.01726778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01338297,"threshold_uncertainty_score":0.02661014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02002786958561972,"score_gpt":0.2192290147981993,"score_spread":0.1992011452125795,"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."}}