{"id":"W1590900504","doi":"10.6846/tku.2009.00643","title":"西文資訊科學期刊文獻之引用分析研究：以JASIS(T)為例","year":2009,"lang":"zh","type":"article","venue":"","topic":"Diverse Approaches in Healthcare and Education Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subject (documents); Citation; Library science; Zipf's law; Bibliometrics; Citation analysis; Information retrieval; Computer science; Mathematics; Statistics","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003344227,0.0002433825,0.0003405584,0.02630769,0.002206622,0.005639173,0.0005851034,0.000432112,0.01343615],"category_scores_gemma":[0.01723121,0.0002592173,0.000416398,0.03462907,0.0008661935,0.003522372,0.001617614,0.0005765156,0.008525889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003739403,"about_ca_system_score_gemma":0.006175632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008365199,"about_ca_topic_score_gemma":0.01744261,"domain_scores_codex":[0.9960471,0.0003379463,0.0005139569,0.0004153446,0.002410965,0.0002747953],"domain_scores_gemma":[0.9762531,0.007207179,0.005151893,0.0009478492,0.009518608,0.0009214114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002400451,0.0001983199,0.3281291,0.003296204,0.0001156273,0.001251717,0.02049952,0.0004299118,0.005397918,0.04267875,0.09897448,0.4987885],"study_design_scores_gemma":[0.00001783525,0.00010536,0.3640274,0.0009746403,0.0001542792,0.001756276,0.02023073,0.001171839,0.007975386,0.004040026,0.5994627,0.00008353607],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5520853,0.01750054,0.007697431,0.008055854,0.001612677,0.0007017417,0.04195218,0.0009178353,0.3694765],"genre_scores_gemma":[0.8238275,0.02058909,0.02291414,0.002081314,0.001142527,0.0008472697,0.02915205,0.0002898099,0.09915627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9736923,"threshold_uncertainty_score":0.04494846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1471313998240091,"score_gpt":0.3928285484523273,"score_spread":0.2456971486283182,"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."}}