{"id":"W2807638568","doi":"10.1109/bigcomp.2018.00065","title":"Article Impact Value for Nearby Citation Network Analysis","year":2018,"lang":"en","type":"article","venue":"","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Impact factor; Citation; Computer science; Metadata; Value (mathematics); Similarity (geometry); Citation impact; Data science; Measure (data warehouse); Information retrieval; Citation analysis; Data mining; World Wide Web; Artificial intelligence; Political science; Machine learning","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","metaresearch"],"domain":"methods","study_design":"theoretical_or_conceptual","genre":"methods","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":"methods","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":[0.003951035,0.0006372025,0.001000252,0.02527406,0.001189405,0.002817955,0.001263088,0.001304356,0.003511215],"category_scores_gemma":[0.03727365,0.0002245606,0.0008235172,0.01664457,0.0008281625,0.003478816,0.001607532,0.0007711768,0.0009633941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001455786,"about_ca_system_score_gemma":0.000957955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00182299,"about_ca_topic_score_gemma":0.001523813,"domain_scores_codex":[0.9967378,0.000741252,0.0002628303,0.0004160498,0.001671385,0.0001707115],"domain_scores_gemma":[0.9829258,0.01171448,0.00145864,0.001025828,0.002395209,0.0004800337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004734813,0.0003642928,0.1117731,0.0006139599,0.0006319334,0.0004230508,0.0004419986,0.1594387,0.007818718,0.1081788,0.008468829,0.6013731],"study_design_scores_gemma":[0.00002892653,0.0001100968,0.02924449,0.0001008492,0.0001374719,0.0004310392,0.0002492222,0.8556088,0.005481324,0.0999513,0.008568025,0.00008834288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2504976,0.002902638,0.7158226,0.0006003113,0.0003164462,0.0005146358,0.002965993,0.002015324,0.02436443],"genre_scores_gemma":[0.8416308,0.000705865,0.1518652,0.00006704,0.0002991217,0.000301569,0.002172835,0.0001755596,0.002782118],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.974726,"threshold_uncertainty_score":0.0208953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6134994399169142,"score_gpt":0.6385578056579951,"score_spread":0.02505836574108089,"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."}}