{"id":"W4232503042","doi":"10.1007/978-1-4614-6170-8_110038","title":"Bibliometrics","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Bibliometrics; Computer science; Library 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":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.001717252,0.00206526,0.002444301,0.02273058,0.001826595,0.009033618,0.001460529,0.001344234,0.2543892],"category_scores_gemma":[0.008850048,0.001164085,0.000727403,0.04125579,0.001369898,0.00854473,0.002704706,0.00214329,0.2453231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002832853,"about_ca_system_score_gemma":0.003332851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006266496,"about_ca_topic_score_gemma":0.01158093,"domain_scores_codex":[0.9973705,0.0003046486,0.0001955063,0.0003226947,0.001682806,0.000123842],"domain_scores_gemma":[0.99755,0.000686298,0.0002089721,0.0003630596,0.001008714,0.0001831135],"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":[0.000008721622,0.00001649722,0.0001899996,0.00031666,0.00001015552,0.000008182617,0.00005251661,0.0001041378,0.00008255888,0.01653347,0.7221181,0.2605591],"study_design_scores_gemma":[0.000002877012,0.000005541209,0.0009625441,0.0003647099,0.000008612311,0.00006243379,0.00006766411,0.0001802457,0.000140772,0.01736199,0.9808317,0.00001101309],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.0005842773,0.0439432,0.008288775,0.004505965,0.003537191,0.0000863493,0.01167711,0.003762861,0.9236142],"genre_scores_gemma":[0.006278793,0.03550084,0.00775219,0.0008615213,0.002524275,0.000158786,0.01276391,0.002259233,0.9319004],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9772694,"threshold_uncertainty_score":0.8510165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06218675745604064,"score_gpt":0.2736000202952544,"score_spread":0.2114132628392138,"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."}}