{"id":"W2359841782","doi":"","title":"Analysis of papers published in Chinese Journal of Optometry & Ophthalmology from 1999 to 2008","year":2009,"lang":"en","type":"article","venue":"Chinese Journal of Optometry & Ophthalmology","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Beijing; Optometry; Bibliometrics; Ophthalmology; Library science; Medicine; History; Archaeology","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005121943,0.0007069625,0.001659084,0.06418001,0.0009754624,0.002313883,0.000830538,0.0004906972,0.005887892],"category_scores_gemma":[0.024217,0.0002341809,0.001681709,0.07484096,0.0003917087,0.001457852,0.0007697131,0.0002098103,0.0008515636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002401488,"about_ca_system_score_gemma":0.004846718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005679877,"about_ca_topic_score_gemma":0.006861757,"domain_scores_codex":[0.9924441,0.0006487786,0.002660127,0.0005827226,0.003262851,0.0004013434],"domain_scores_gemma":[0.9590397,0.01054399,0.01504478,0.0006897851,0.01262825,0.002053515],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009925794,0.0001421667,0.7744731,0.03178034,0.002565896,0.001828007,0.001675312,0.0003824505,0.002194398,0.0004494885,0.01443033,0.1690859],"study_design_scores_gemma":[0.00005209704,0.0001642798,0.9800799,0.001569718,0.001292919,0.0008382655,0.00114341,0.0001791504,0.0006808664,0.0001476839,0.01382226,0.00002935104],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7182111,0.1918757,0.0006255957,0.002246919,0.001182283,0.0007112412,0.06914742,0.0001550704,0.01584472],"genre_scores_gemma":[0.8847644,0.07652964,0.0018434,0.0004844468,0.001167573,0.0006675383,0.02952565,0.00004342795,0.004973867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9948781,"threshold_uncertainty_score":0.02708775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0189893928125003,"score_gpt":0.388896739957076,"score_spread":0.3699073471445757,"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."}}