{"id":"W4405925789","doi":"10.2196/56663","title":"Use of 4 Open-Ended Text Responses to Help Identify People at Risk of Gaming Disorder: Preregistered Development and Usability Study Using Natural Language Processing","year":2024,"lang":"en","type":"article","venue":"JMIR Serious Games","topic":"Mental Health via Writing","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Marcus och Amalia Wallenbergs minnesfond","keywords":"Usability; Natural (archaeology); Computer science; Psychology; Human–computer interaction; Cognitive psychology; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0008390452,0.0002321109,0.0004798171,0.0002140444,0.0002118359,0.0001829044,0.0002788164,0.00007569245,0.0000640954],"category_scores_gemma":[0.0001684411,0.0002169405,0.00004445797,0.000433524,0.00008033123,0.0003453147,0.0006946365,0.0002062926,0.000008624249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002244732,"about_ca_system_score_gemma":0.0001208624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002659963,"about_ca_topic_score_gemma":0.005768977,"domain_scores_codex":[0.9974008,0.000490944,0.0007801213,0.0006521292,0.0002911618,0.0003848457],"domain_scores_gemma":[0.9986966,0.0003969141,0.000293656,0.0004379209,0.00006335831,0.0001115304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001063934,0.0005462684,0.5648314,0.001822423,0.000123769,0.000045587,0.1982793,0.000007007321,0.009811784,0.000005930653,0.00007740445,0.2233852],"study_design_scores_gemma":[0.0006846584,0.0002528079,0.9511113,0.000680069,0.0000468136,0.00005130644,0.04424569,0.0004823012,0.001811387,0.000004952414,0.0003876806,0.0002410798],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930589,0.003967,0.00002917042,0.00005177372,0.0002762488,0.002436104,0.00004413369,0.00007137134,0.00006533266],"genre_scores_gemma":[0.9954797,0.000005784766,0.002942313,0.00002986186,0.00002483127,0.0001937341,0.000007003036,0.00004322567,0.001273529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3862799,"threshold_uncertainty_score":0.8846576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05913620664303057,"score_gpt":0.4255477968696926,"score_spread":0.366411590226662,"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."}}