{"id":"W2888619884","doi":"10.2196/ijmr.9359","title":"Calorie Estimation From Pictures of Food: Crowdsourcing Study","year":2018,"lang":"en","type":"article","venue":"Interactive Journal of Medical Research","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Calorie; Respondent; Food energy; Ground truth; Body mass index; Statistics; Computer science; Range (aeronautics); Software; Environmental health; Artificial intelligence; Mathematics; Medicine; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005738508,0.0006204117,0.0006421681,0.001358578,0.001359466,0.001046279,0.0009881703,0.001270681,0.001472642],"category_scores_gemma":[0.02481584,0.000269719,0.0007745679,0.0008975716,0.0009043782,0.001201748,0.001931189,0.00080317,0.0009674039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000878203,"about_ca_system_score_gemma":0.0007172002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01107592,"about_ca_topic_score_gemma":0.01203148,"domain_scores_codex":[0.9958708,0.001927099,0.0001765291,0.0008100371,0.0009994017,0.0002162407],"domain_scores_gemma":[0.9765071,0.01483298,0.001457092,0.003240591,0.003229965,0.0007322827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00661434,0.006484863,0.6069379,0.002481444,0.00114849,0.003694185,0.0890016,0.01009943,0.02689381,0.002598027,0.01813777,0.2259082],"study_design_scores_gemma":[0.0006008606,0.002654633,0.8319287,0.0004577113,0.00042159,0.002362816,0.03977435,0.06927174,0.01498874,0.005930154,0.03108262,0.0005260531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992792,0.0001375849,0.00351486,0.0002322096,0.00003975352,0.0002614743,0.0006313632,0.00007439738,0.002316213],"genre_scores_gemma":[0.9918374,0.0001127437,0.005374954,0.0002741378,0.00006412809,0.0002689549,0.0007497562,0.00004665036,0.001271333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01107592,"threshold_uncertainty_score":0.03034854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09702204511123481,"score_gpt":0.4889720191446199,"score_spread":0.3919499740333851,"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."}}