{"id":"W6885865672","doi":"10.1371/journal.pone.0279275.s004","title":"Advertising expenditures on child-targeted products&lt;sup&gt;†&lt;/sup&gt; across all media (excluding digital media) in 2016 by Health Canada’s proposed nutrient profile model (NPM) classification and by geographic region.","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Obesity, Physical Activity, Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nutrient; Social media; Digital media; Location; Digital advertising","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":[0.0008150553,0.000750693,0.0004024572,0.003847369,0.0007803604,0.001716576,0.001198546,0.0004342191,0.02455296],"category_scores_gemma":[0.002902744,0.0003621638,0.001594483,0.006918025,0.0002842988,0.00126928,0.0008678383,0.001326242,0.005594833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01323297,"about_ca_system_score_gemma":0.02156257,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8930135,"about_ca_topic_score_gemma":0.9361551,"domain_scores_codex":[0.9986622,0.0001080064,0.00006832011,0.00009496857,0.0007783053,0.0002880526],"domain_scores_gemma":[0.997736,0.0001341163,0.0002314175,0.00007036422,0.001507613,0.0003205357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004535819,0.0001119408,0.06498575,0.0009864197,0.0002317618,0.0000775008,0.0002215292,0.002760613,0.0002742482,0.01055737,0.8596773,0.05966188],"study_design_scores_gemma":[0.0001477604,0.00007728762,0.2955483,0.0008870767,0.0002606267,0.0001549938,0.0006099691,0.00453751,0.0009973649,0.002003895,0.6946915,0.00008368309],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.02900618,0.002545573,0.001485253,0.003307475,0.0004250068,0.0003174821,0.8625026,0.000599336,0.09981116],"genre_scores_gemma":[0.2149404,0.005900718,0.006582441,0.001814972,0.0001237021,0.0004579572,0.6585867,0.0002714173,0.1113217],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1069865,"threshold_uncertainty_score":0.2152331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03914524675682785,"score_gpt":0.2776279253584545,"score_spread":0.2384826786016267,"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."}}