{"id":"W6967312700","doi":"10.5281/zenodo.10032032","title":"Conference proceedings as a source of scientific information: A bibliometric analysis","year":2008,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Scientific literature; Bibliometrics; Natural science; Natural (archaeology); Scientific evidence; Scientific progress","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0183055,0.0006575906,0.001836932,0.1163528,0.001983567,0.009256155,0.001186188,0.001122618,0.004046094],"category_scores_gemma":[0.1261615,0.0003409667,0.001333698,0.2265729,0.001349076,0.007543263,0.003623159,0.001027982,0.001238137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002691071,"about_ca_system_score_gemma":0.00239198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002250592,"about_ca_topic_score_gemma":0.002114429,"domain_scores_codex":[0.9668815,0.007081253,0.003330759,0.001479791,0.02040394,0.0008227855],"domain_scores_gemma":[0.8590946,0.09472635,0.0176633,0.005285878,0.02054305,0.002686745],"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":[0.0004684066,0.0002648126,0.3816054,0.005145247,0.001805837,0.0007075501,0.006416729,0.005796333,0.001554211,0.03010135,0.02279186,0.5433423],"study_design_scores_gemma":[0.0001098915,0.0004730454,0.7680795,0.001530567,0.002215647,0.002722905,0.007659282,0.02099495,0.004082751,0.03253746,0.1592833,0.0003107975],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.766108,0.07154372,0.02462705,0.004922267,0.001017308,0.0007279235,0.0181245,0.0009498219,0.1119794],"genre_scores_gemma":[0.9520043,0.02409721,0.01021596,0.0001304936,0.001019102,0.0003846641,0.00783939,0.0001927611,0.004116077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8836472,"threshold_uncertainty_score":0.09680986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3452247985647393,"score_gpt":0.4207023654068284,"score_spread":0.07547756684208917,"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."}}