{"id":"W2921515576","doi":"10.1017/9781108149938","title":"Clinical Neuroendocrinology: An Introduction","year":2019,"lang":"en","type":"book","venue":"","topic":"Neuroendocrine Tumor Research Advances","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Variety (cybernetics); Neuroendocrinology; Subject (documents); Resource (disambiguation); Context (archaeology); Engineering ethics; Graduate students; Computer science; Psychology; Data science; Medicine; Library science; Engineering; Artificial intelligence; Pedagogy; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004195291,0.001195377,0.0009716706,0.001854145,0.0007600674,0.003022541,0.0008065238,0.001744417,0.05508909],"category_scores_gemma":[0.001551376,0.0005148646,0.0005773666,0.001262697,0.0007684632,0.002427905,0.0016754,0.004214831,0.03867351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007425157,"about_ca_system_score_gemma":0.001245931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007893389,"about_ca_topic_score_gemma":0.001333924,"domain_scores_codex":[0.9997099,0.00005886627,0.00002745007,0.00005413383,0.0001260146,0.000023653],"domain_scores_gemma":[0.9994855,0.0002079593,0.00003616211,0.00002362873,0.0001328535,0.0001138241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004724728,0.000111362,0.0001591809,0.001224088,0.000008912977,0.0006315241,0.0002918227,0.0004009742,0.001690594,0.01306399,0.7619681,0.2204022],"study_design_scores_gemma":[0.000003626805,0.00002482979,0.0001795632,0.0004628007,0.000001734726,0.001049428,0.00004083785,0.00005243969,0.00005616543,0.003356444,0.9947653,0.000006927655],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002173078,0.4066279,0.01678417,0.03373131,0.0846128,0.0007333052,0.001851632,0.001608419,0.4518774],"genre_scores_gemma":[0.00656785,0.307728,0.02217807,0.03103582,0.03969908,0.0009419636,0.0019592,0.0007976452,0.5890924],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05508909,"threshold_uncertainty_score":0.1842914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0505989914951047,"score_gpt":0.3995155765815211,"score_spread":0.3489165850864164,"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."}}