{"id":"W3048692611","doi":"","title":"An assessment of accuracy improvement by adaptive survey design : [Une évaluation de l’amélioration de l’exactitude au moyen d’un plan de sondage adaptatif]","year":2019,"lang":"fr","type":"article","venue":"Survey methodology","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"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"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.0711055,0.0004341656,0.0008988967,0.0002246681,0.0001889579,0.00006024484,0.0003417651,0.0006692222,0.0005279229],"category_scores_gemma":[0.009548865,0.0004869015,0.0001205946,0.0005085749,0.0001218949,0.0004895787,0.00006816075,0.000509869,0.00002001912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001299936,"about_ca_system_score_gemma":0.001945672,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06428429,"about_ca_topic_score_gemma":0.01316822,"domain_scores_codex":[0.9463636,0.05005946,0.001399017,0.00067219,0.0005831802,0.0009225902],"domain_scores_gemma":[0.9718388,0.02506964,0.001451756,0.0006740989,0.0007247307,0.0002410007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002257475,0.001872262,0.4749681,0.0005899101,0.0007319284,0.000009736225,0.01799623,0.1381544,0.1970846,0.01409374,0.001414386,0.1508272],"study_design_scores_gemma":[0.0009555154,0.00102411,0.6334735,0.00004908647,0.0001526626,0.00001167492,0.0003882887,0.3434464,0.009105771,0.01104394,0.00004113797,0.0003079974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4549632,0.00008815323,0.5429592,0.0001501448,0.0004336335,0.0008647259,0.0004431737,0.00002832812,0.00006942321],"genre_scores_gemma":[0.5495072,0.00005949864,0.4487942,0.00007200793,0.00006262582,0.00004446303,0.001203543,0.00004890958,0.0002076299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.205292,"threshold_uncertainty_score":0.9997582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4336167277882685,"score_gpt":0.4782844676439482,"score_spread":0.04466773985567962,"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."}}