{"id":"W2734653099","doi":"10.29173/cais300","title":"Making Sense of Sense-Making: Information Behavior Researchers Construct an ‘Author’","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Discourse Analysis in Language Studies","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Construct (python library); Constructive; Meaning (existential); Humanities; Sociology; Psychology; Epistemology; Philosophy; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001090124,0.000451448,0.0008846297,0.000441107,0.0004335534,0.004650272,0.001046268,0.0002403763,0.0008074703],"category_scores_gemma":[0.01077007,0.0003695353,0.0003692778,0.0003297154,0.003881617,0.02192552,0.0007686792,0.000533628,0.00001781158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009644444,"about_ca_system_score_gemma":0.0003064946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002412271,"about_ca_topic_score_gemma":0.0001711723,"domain_scores_codex":[0.9966737,0.00009927888,0.001217924,0.0003336979,0.0009705974,0.0007047993],"domain_scores_gemma":[0.9340976,0.0002098951,0.001865578,0.0003454521,0.06334146,0.0001399563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001872939,0.000452136,0.03438852,0.001993746,0.0008682644,0.000008107058,0.5329422,0.00001363165,0.003888957,0.3796642,0.007887083,0.03770589],"study_design_scores_gemma":[0.001418467,0.001361847,0.05045268,0.004349154,0.002195085,0.0001855034,0.7228622,0.001781698,0.01348947,0.0103712,0.1900526,0.001480085],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9219451,0.0008015538,0.000006533382,0.002383242,0.0003640087,0.0006849553,0.0006285183,0.00003704974,0.07314906],"genre_scores_gemma":[0.9960508,0.0001629735,0.0005623279,0.0001548546,0.0002516969,0.00005384266,0.00001224657,0.00003496722,0.002716261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3692929,"threshold_uncertainty_score":0.9998757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07572338016876025,"score_gpt":0.3265171207967932,"score_spread":0.2507937406280329,"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."}}