{"id":"W2405560216","doi":"","title":"Factorial correspondence analysis applied to citation contexts","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Web visibility and informetrics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Rhetorical question; Citation; Factorial; Computer science; Factorial analysis; Relation (database); Linguistics; Natural language processing; Citation analysis; Information retrieval; Artificial intelligence; Mathematics; Statistics; World Wide Web; Data mining; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009846407,0.0003660162,0.0005728312,0.001176506,0.0002592213,0.001254295,0.00361949,0.0003649374,0.00006208802],"category_scores_gemma":[0.00483205,0.000394211,0.0002937514,0.003776979,0.0001147688,0.0004083125,0.003091106,0.0006266398,0.0002156791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003256995,"about_ca_system_score_gemma":0.0007454019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007779092,"about_ca_topic_score_gemma":0.001112423,"domain_scores_codex":[0.9942355,0.002393049,0.0007465941,0.001149251,0.001054588,0.0004210311],"domain_scores_gemma":[0.9891372,0.001841764,0.0005942069,0.00367767,0.004312207,0.0004369432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000950516,0.0008973993,0.003141939,0.0001707306,0.0006561015,0.000007249096,0.06320465,0.01000743,0.00125944,0.6888425,0.01203685,0.2196807],"study_design_scores_gemma":[0.003994866,0.00001068134,0.07224029,0.00160931,0.0009728733,0.00001351577,0.0006145275,0.6184844,0.05917995,0.1358298,0.1018137,0.005236068],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03134205,0.0001439374,0.9249486,0.002230583,0.0008403909,0.0005883079,0.00005591873,0.0003286161,0.03952163],"genre_scores_gemma":[0.8829195,0.00003110135,0.1127891,0.0002505252,0.00004952186,0.00007900313,0.0003122627,0.00001999902,0.003549029],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8515775,"threshold_uncertainty_score":0.999851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02594978492706029,"score_gpt":0.2576738828825945,"score_spread":0.2317240979555342,"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."}}