{"id":"W4307497500","doi":"10.2196/38480","title":"A Tailored Gender-Sensitive mHealth Weight Loss Intervention (I-GENDO): Development and Process Evaluation","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ruhr-Universität Bochum; Bundesministerium für Bildung und Forschung","keywords":"Overweight; Psychological intervention; mHealth; Obesity; Weight loss; Intervention (counseling); Medicine; Gerontology; Clinical psychology; Psychology; Physical therapy; Psychiatry; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01261871,0.0001930673,0.0003067827,0.000622849,0.006631274,0.00001822772,0.0002601331,0.0001247713,0.001093576],"category_scores_gemma":[0.0002030705,0.0001835083,0.00004643452,0.001106647,0.0001551994,0.0003146058,0.0005003989,0.002108362,0.0003112896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002141142,"about_ca_system_score_gemma":0.003412843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001427175,"about_ca_topic_score_gemma":0.0001323817,"domain_scores_codex":[0.9907024,0.004461416,0.001091356,0.000521542,0.001909906,0.001313376],"domain_scores_gemma":[0.9965301,0.0006689646,0.0004349073,0.0003407163,0.001469404,0.000555938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001811269,0.001733026,0.0194314,0.009175186,0.0001246765,0.00001427497,0.3363472,0.00005917174,0.0000849014,0.03076532,0.03739063,0.563063],"study_design_scores_gemma":[0.01090952,0.001448624,0.2631209,0.0005022353,0.00003771766,0.00005148237,0.1823486,0.01505784,0.0004444121,0.01621409,0.5091459,0.0007186912],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701983,0.0006297966,0.001058248,0.002772896,0.000418993,0.01390162,0.00009993109,0.0001260771,0.01079416],"genre_scores_gemma":[0.9129804,0.0001477759,0.0001865568,0.0004532545,0.0001316751,0.08522747,0.0004015647,0.00003051975,0.0004407963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5623443,"threshold_uncertainty_score":0.9998196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2113271186976644,"score_gpt":0.5640089423798672,"score_spread":0.3526818236822028,"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."}}