{"id":"W7099092786","doi":"","title":"Fruit and Vegetable Consumption and Body Mass Index: A Quantile Regression Approach","year":2016,"lang":"en","type":"article","venue":"","topic":"Sunflower and Safflower Cultivation","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantile regression; Quantile; Body mass index; Consumption (sociology); Multivariate statistics; Linear regression; Regression analysis; Ordinary least squares","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005670454,0.0005610366,0.0008868322,0.001332575,0.0003596144,0.0008927117,0.001671151,0.0007253299,0.00543803],"category_scores_gemma":[0.01237822,0.0003290247,0.001666824,0.002552949,0.0006280557,0.0005536357,0.0007910456,0.001292366,0.00079844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00100174,"about_ca_system_score_gemma":0.0009996092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03111864,"about_ca_topic_score_gemma":0.0114136,"domain_scores_codex":[0.9975541,0.001639861,0.0000626864,0.0003565878,0.0002122855,0.0001745349],"domain_scores_gemma":[0.9945965,0.004118805,0.0005191911,0.0003972717,0.0002649284,0.0001033115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000690488,0.0004134455,0.6798787,0.0004346417,0.003279309,0.0008228614,0.001093472,0.1435847,0.001937527,0.03408375,0.005964268,0.1278169],"study_design_scores_gemma":[0.00009396424,0.0003469517,0.3799053,0.0001566806,0.000931163,0.00047454,0.0006564878,0.555976,0.000795115,0.05138461,0.009188991,0.00009017152],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5407163,0.0040433,0.4363735,0.002807195,0.0001284399,0.0005005003,0.004774571,0.0007237622,0.009932307],"genre_scores_gemma":[0.9591231,0.001216854,0.03451952,0.0001851133,0.00008247169,0.0002622825,0.001348258,0.00009757313,0.003164792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03111864,"threshold_uncertainty_score":0.06187499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02751733757643766,"score_gpt":0.2323827225190729,"score_spread":0.2048653849426352,"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."}}