{"id":"W2954528668","doi":"","title":"Project Leapp(Learning to Eat App): Developing an Ipad-Based Video Modelling Intervention to Increase Food Variety in Children with Autism Spectrum Disorder.","year":2018,"lang":"en","type":"article","venue":"INSAR 2018 Annual Meeting","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital","funders":"","keywords":"Autism spectrum disorder; Intervention (counseling); Variety (cybernetics); Autism; Psychology; Typically developing; Mobile apps; Developmental psychology; Computer science; World Wide Web; Artificial intelligence; Psychiatry","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":[],"consensus_categories":[],"category_scores_codex":[0.0009753053,0.0009694983,0.0003606585,0.000328619,0.0005543206,0.0006702077,0.001272365,0.0008598719,0.008052913],"category_scores_gemma":[0.002294776,0.0002136189,0.0007002625,0.0001395216,0.0003787182,0.0009443388,0.001980335,0.001414413,0.001730446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005282366,"about_ca_system_score_gemma":0.001847018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005490972,"about_ca_topic_score_gemma":0.01201589,"domain_scores_codex":[0.9995502,0.0001534773,0.00002246101,0.00009214488,0.0001081254,0.00007354098],"domain_scores_gemma":[0.9994578,0.0001894766,0.00002826211,0.00002893763,0.00008841346,0.0002071412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004443571,0.03379524,0.01911856,0.003131759,0.0002830455,0.001824934,0.009349028,0.001480331,0.02691763,0.001270744,0.1094754,0.7889097],"study_design_scores_gemma":[0.02193674,0.06609657,0.2530423,0.006422209,0.002558301,0.009798942,0.03306673,0.02913121,0.09428696,0.0129338,0.4698101,0.0009161559],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9128137,0.001555027,0.02766874,0.004555801,0.0008676682,0.006712713,0.0043337,0.004995418,0.03649726],"genre_scores_gemma":[0.6484712,0.003258009,0.269251,0.003394578,0.0001454649,0.02724286,0.005904237,0.0007896629,0.04154298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008052913,"threshold_uncertainty_score":0.02693969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02742283227661181,"score_gpt":0.2985841235304702,"score_spread":0.2711612912538584,"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."}}