{"id":"W4386697636","doi":"10.47854/anthropen.v1i1.52071","title":"Big data","year":2023,"lang":"fr","type":"article","venue":"Anthropen","topic":"Diverse Cultural and Historical Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Big data; Humanities; Diction; Philosophy; Soul; Sociology; Epistemology; Computer science; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01142219,0.001691595,0.001890212,0.009189621,0.001892903,0.01269719,0.003413098,0.002587203,0.1208839],"category_scores_gemma":[0.06394551,0.00116277,0.002150732,0.01473775,0.001370828,0.009740951,0.007304991,0.004271284,0.1080773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002761249,"about_ca_system_score_gemma":0.009560546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005103398,"about_ca_topic_score_gemma":0.00295762,"domain_scores_codex":[0.9811474,0.004800466,0.002794269,0.003763195,0.006528817,0.0009659309],"domain_scores_gemma":[0.9453828,0.01333428,0.0033029,0.01978019,0.01410416,0.004095661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003140853,0.00006195239,0.004086806,0.00192032,0.0002927871,0.0001423,0.0003632854,0.0008628395,0.0009429936,0.03955192,0.8039256,0.1475352],"study_design_scores_gemma":[0.00004017394,0.00003090574,0.003119301,0.0006513537,0.00004024146,0.0001209801,0.0002592963,0.0009709859,0.0004960505,0.02278773,0.9714325,0.00005051513],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.004110318,0.01148997,0.08132817,0.03579538,0.008266525,0.002474921,0.6218023,0.02970278,0.2050297],"genre_scores_gemma":[0.05103584,0.01284653,0.07976831,0.01187814,0.004567719,0.004838496,0.7515091,0.007391756,0.07616407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1208839,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4343153380268028,"score_gpt":0.3942174746644727,"score_spread":0.04009786336233018,"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."}}