{"id":"W3006679052","doi":"10.1080/02763869.2020.1688621","title":"An Investigation of the Backgrounds of Health Sciences Librarians","year":2020,"lang":"en","type":"article","venue":"Medical Reference Services Quarterly","topic":"Web and Library Services","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Appeal; Variety (cybernetics); Medical education; Professional development; Field (mathematics); Work (physics); Biomedical sciences; Library science; Medicine; Political science; Nursing; Computer science; Engineering","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":[0.0006434407,0.0001301395,0.0002763595,0.00005158474,0.0001418999,0.0001113028,0.003909147,0.0000923793,0.00009784537],"category_scores_gemma":[0.000008818097,0.00008263984,0.00004961713,0.001108866,0.0002798552,0.001984178,0.0001413245,0.0001852717,0.00001048468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005138283,"about_ca_system_score_gemma":0.0007138029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006883474,"about_ca_topic_score_gemma":0.0001662417,"domain_scores_codex":[0.9973213,0.0004347615,0.0005653058,0.000385205,0.001047472,0.0002459659],"domain_scores_gemma":[0.9985932,0.0001063816,0.0004105657,0.000491989,0.00005514095,0.0003427807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003457618,0.0002883926,0.1083351,0.002655009,0.000055994,0.000005065589,0.146936,0.00005423665,0.00463196,0.4382131,0.0004510489,0.2983395],"study_design_scores_gemma":[0.001500165,0.01179938,0.5955554,0.001625192,0.00002286984,0.00001390864,0.01584255,0.3010547,0.007591548,0.06090929,0.003257896,0.0008271232],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9438472,0.0002427355,0.006604124,0.04776195,0.0001882317,0.0001529544,0.000007366065,0.0001055046,0.001089951],"genre_scores_gemma":[0.9865243,0.00001203058,0.003150811,0.01023477,0.00005868269,0.000002969883,0.00000647572,0.000004926959,0.000004982257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4872203,"threshold_uncertainty_score":0.7264232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0337410500598565,"score_gpt":0.26364457849044,"score_spread":0.2299035284305835,"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."}}