{"id":"W4402465638","doi":"10.29173/cais1855","title":"“O Author, Where Art Thou?” An Analysis of Affiliation Indexing in Canadian Journals and Bibliometric Research Potential","year":2024,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Publishing and Scholarly Communication","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Thou; Bibliometrics; Search engine indexing; Library science; History; Computer science; Information retrieval; Philosophy; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.009510193,0.0003873851,0.000570717,0.02745673,0.008089417,0.008609795,0.001528802,0.0006623297,0.006984134],"category_scores_gemma":[0.1004903,0.0002272424,0.0006377037,0.0693598,0.003749112,0.002436276,0.003212705,0.0007399149,0.0008150983],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03311459,"about_ca_system_score_gemma":0.07246624,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9022926,"about_ca_topic_score_gemma":0.9162534,"domain_scores_codex":[0.9801296,0.002167313,0.001109906,0.0009356283,0.01341028,0.002247256],"domain_scores_gemma":[0.9266306,0.01628436,0.01038186,0.001832991,0.04022716,0.004643005],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002930619,0.00005084257,0.6806449,0.001114472,0.0002468103,0.0005085749,0.02292806,0.0008756216,0.001642705,0.07908276,0.02849744,0.1841147],"study_design_scores_gemma":[0.00002202383,0.00005519772,0.8861144,0.0005960508,0.0003082442,0.0003690523,0.02156973,0.00246651,0.001678796,0.008377816,0.0783122,0.0001298979],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7502782,0.007073732,0.003777385,0.0142072,0.0005842154,0.0002397051,0.009376965,0.0002554678,0.2142072],"genre_scores_gemma":[0.9896734,0.001315464,0.002583754,0.0003174592,0.000085325,0.00003282204,0.0009627328,0.00005820752,0.004970869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9904898,"threshold_uncertainty_score":0.2402644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0907307670514184,"score_gpt":0.3394581800387351,"score_spread":0.2487274129873167,"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."}}