{"id":"W4404816234","doi":"10.2196/59215","title":"Novel Profiles of Family Media Use: Latent Profile Analysis","year":2024,"lang":"en","type":"article","venue":"JMIR Pediatrics and Parenting","topic":"Child Development and Digital Technology","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Preprint; Computer science; World Wide Web","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":[0.003602302,0.0004754453,0.0004108082,0.002624939,0.000947592,0.002129292,0.0005813387,0.0005324401,0.003581155],"category_scores_gemma":[0.01450651,0.0002534239,0.001077357,0.002295981,0.0006786644,0.001566329,0.001679978,0.001006833,0.0004350539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001207152,"about_ca_system_score_gemma":0.001168461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008310118,"about_ca_topic_score_gemma":0.005858583,"domain_scores_codex":[0.9975491,0.001459196,0.0001610161,0.0003268074,0.0002429486,0.000260952],"domain_scores_gemma":[0.9915801,0.005208035,0.001385101,0.0008270218,0.0006954009,0.0003042873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001666081,0.0001834156,0.9687234,0.00004280993,0.0001218287,0.00008145123,0.003265426,0.001285271,0.0004711651,0.002385337,0.0004772426,0.02279598],"study_design_scores_gemma":[0.00003491485,0.0002231966,0.8900512,0.0001083776,0.0001249012,0.0003877859,0.01034922,0.08441707,0.0007702349,0.01148122,0.001991163,0.00006075354],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969036,0.0001061774,0.02749616,0.0002167675,0.000007610719,0.0002118964,0.001523334,0.00004956956,0.001352522],"genre_scores_gemma":[0.9941533,0.00003807525,0.004332514,0.00001091314,0.000003984744,0.0001726496,0.001090873,0.00000691049,0.0001907499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008310118,"threshold_uncertainty_score":0.01905102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04527933972175393,"score_gpt":0.305364665541239,"score_spread":0.2600853258194851,"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."}}