{"id":"W2980909041","doi":"10.1002/pra2.50","title":"Exploring the function of citations in ancient Chinese literature","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Constructive; Normative; Function (biology); Epistemology; History; Sociology; Literature; Philosophy; Art; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.0166839,0.00005347352,0.0001308811,0.01809899,0.000217932,0.0004957516,0.001180685,0.00006219045,0.000002222591],"category_scores_gemma":[0.05199819,0.00002685136,0.00004078468,0.1424142,0.0001910308,0.004525999,0.0003272829,0.0001399518,0.000006029778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001296528,"about_ca_system_score_gemma":0.0001068558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000381157,"about_ca_topic_score_gemma":0.000001692336,"domain_scores_codex":[0.9960704,0.000005740031,0.0005111105,0.00014899,0.003053893,0.0002098859],"domain_scores_gemma":[0.9884236,0.0006666231,0.0007726178,0.0001507741,0.009959797,0.00002655383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001167088,0.00001822822,0.8658893,0.00001897878,0.000003817019,1.977492e-9,0.001534685,0.00002192709,0.009324969,0.09599794,0.0003900845,0.02678838],"study_design_scores_gemma":[0.0003390363,0.00009345629,0.9495125,0.00001962712,0.000002701544,6.70162e-7,0.002862838,0.002817743,0.005392198,0.03269012,0.006218046,0.00005106627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929649,0.00003554671,0.00003375407,0.003112485,0.0003203459,0.0004107535,0.00001125858,0.000008605288,0.003102403],"genre_scores_gemma":[0.9996049,0.0000373021,0.0001199678,0.00005996368,0.000005822661,0.00003732266,4.961779e-7,0.000001165604,0.0001329914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1243152,"threshold_uncertainty_score":0.99303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1915723729450913,"score_gpt":0.4298715034228472,"score_spread":0.2382991304777559,"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."}}