{"id":"W2065349426","doi":"10.3395/reciis.v2i1.160en","title":"The culture of numbers: the origins and development of statistics on science","year":2008,"lang":"en","type":"article","venue":"Reciis","topic":"Philosophy and History of Science","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Civilization; Productivity; Statistics; Context (archaeology); Social science; Sociology; Political science; Economics; Mathematics; Geography; Economic growth; Law","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0001911724,0.00003718424,0.00005011608,0.00001769345,0.001264132,0.00001813482,0.0001863442,0.000006499205,0.00003239061],"category_scores_gemma":[0.00002990167,0.00001779245,0.00000809143,0.00003346977,0.002816922,0.00006461508,0.00002027499,0.00004412454,0.000006801669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002386975,"about_ca_system_score_gemma":0.000120075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003877243,"about_ca_topic_score_gemma":0.0001259804,"domain_scores_codex":[0.999526,0.000007819692,0.00009748182,0.00006949466,0.0002251112,0.00007415119],"domain_scores_gemma":[0.9996835,0.00005631437,0.00006118949,0.00009361195,0.00008572141,0.00001963653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008005423,0.00002408702,0.0000382652,0.000007581797,0.000004557108,5.630453e-7,0.2059867,0.000001037369,0.0002145741,0.7812949,0.003453014,0.008966653],"study_design_scores_gemma":[0.00006002789,0.00006488795,0.0005436382,0.00001798532,0.000002619716,0.000002254142,0.003825802,0.000009492645,0.001450804,0.004135719,0.9898372,0.00004955701],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4190293,0.0006584663,0.0001040763,0.0005722844,0.0007792971,0.0002001901,0.00007386367,0.00001756767,0.5785649],"genre_scores_gemma":[0.9977075,0.00007974183,0.0006796731,0.00005584459,0.00004583327,0.000001477707,3.337954e-7,0.000001425982,0.00142818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9863842,"threshold_uncertainty_score":0.9998968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07383829710951338,"score_gpt":0.2446250877662426,"score_spread":0.1707867906567292,"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."}}