{"id":"W4206719805","doi":"10.5539/jel.v11n1p147","title":"Academic Inbreeding: A Risk or Benefit for Universities?","year":2022,"lang":"en","type":"article","venue":"Journal of Education and Learning","topic":"Higher Education Governance and Development","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inbreeding; Higher education; Psychology; Qualitative research; Medical education; Sociology; Political science; Social science; Medicine; Demography; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001046996,0.00003217195,0.00006479294,0.000101735,0.001132082,0.00002857816,0.00008933472,0.00002162976,0.0006685924],"category_scores_gemma":[0.0002442632,0.00003016358,0.00002689443,0.000167777,0.00002354616,0.000179528,0.00001500605,0.0003563356,0.000001026896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000283635,"about_ca_system_score_gemma":0.002005595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001397426,"about_ca_topic_score_gemma":0.000014607,"domain_scores_codex":[0.9994206,0.00009539319,0.0001424223,0.00005108352,0.0002033073,0.00008715509],"domain_scores_gemma":[0.9991986,0.0001880105,0.0003790042,0.00001783632,0.0001427372,0.00007376832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002386806,0.0001941699,0.1226791,0.00001917576,0.00005900873,0.000001106797,0.5961215,0.0008299737,0.00004961455,0.03172539,0.06846757,0.1796148],"study_design_scores_gemma":[0.000133272,0.00006747477,0.01387605,0.000009795862,0.000009942922,0.000005416844,0.2502293,0.000005825628,0.000001682862,0.0004342449,0.7351922,0.00003481592],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898332,0.0005270892,0.0001769855,0.004770506,0.001242002,0.00006798939,0.000001172183,0.000005991572,0.003375076],"genre_scores_gemma":[0.9425229,0.0005252434,0.001386823,0.0004119562,0.0005188857,0.000006720444,0.000001206301,0.00000396475,0.05462223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6667246,"threshold_uncertainty_score":0.870717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02727375448314537,"score_gpt":0.3532087633661343,"score_spread":0.3259350088829889,"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."}}