{"id":"W1521589337","doi":"10.1920/wp.ifs.2006.0621","title":"Measurement errors in recall food consumption data","year":2017,"lang":"en","type":"paratext","venue":"","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Recall; Food consumption; Computer science; Psychology; Cognitive psychology; Economics; Agricultural economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05301476,0.0006143387,0.0009933179,0.002318578,0.0009365326,0.002305771,0.001984103,0.001559825,0.004573517],"category_scores_gemma":[0.2690872,0.0006367714,0.0009218946,0.006875092,0.001964298,0.002611251,0.00211561,0.002415133,0.001320391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002086093,"about_ca_system_score_gemma":0.001364051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009080724,"about_ca_topic_score_gemma":0.005650015,"domain_scores_codex":[0.9158648,0.04701817,0.00953079,0.007499397,0.0188661,0.001220654],"domain_scores_gemma":[0.7618998,0.1520421,0.0286818,0.04030699,0.0165223,0.0005471001],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008236631,0.0004096179,0.3688956,0.003330124,0.002004737,0.0006895167,0.007538996,0.02351753,0.001196061,0.2812471,0.06968362,0.2406635],"study_design_scores_gemma":[0.0003290944,0.000412154,0.3007213,0.004104622,0.0009425728,0.001675354,0.004920598,0.0352327,0.01052056,0.3739607,0.2668025,0.0003778774],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2189568,0.01662561,0.6520261,0.02308056,0.004367264,0.001682206,0.03149387,0.0008965643,0.05087108],"genre_scores_gemma":[0.8978826,0.004168117,0.06867424,0.003268454,0.0008605359,0.001311839,0.01352162,0.0001831467,0.01012947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9469852,"threshold_uncertainty_score":0.2803723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2068136926868315,"score_gpt":0.2744831458968099,"score_spread":0.06766945320997847,"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."}}