{"id":"W6890175109","doi":"10.34990/fk2/fqn6ho","title":"Replication Data for: Mobile Health App - Research and Recover","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Replication (statistics); Health data; Mobile apps; Raw data; mHealth; Mobile device; Mobile computing; Digital health","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":[0.008672981,0.00229757,0.001684807,0.002743682,0.001953172,0.003325741,0.004429562,0.002601988,0.1631733],"category_scores_gemma":[0.06263182,0.001320456,0.001990884,0.005837652,0.0008960795,0.002197944,0.00323846,0.002869967,0.1206997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002006159,"about_ca_system_score_gemma":0.006578067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04212699,"about_ca_topic_score_gemma":0.07187272,"domain_scores_codex":[0.9936705,0.001730542,0.0009610683,0.00144654,0.001641732,0.0005495893],"domain_scores_gemma":[0.9723017,0.007508128,0.001908212,0.009119053,0.008198621,0.0009643661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001532679,0.00002812107,0.00106967,0.0006205618,0.00005583014,0.00001545047,0.00004874981,0.0001307746,0.00007010921,0.0006411402,0.9948369,0.002329438],"study_design_scores_gemma":[0.001402885,0.00009188352,0.01181096,0.0007629989,0.0001759549,0.00008286518,0.0002383259,0.0003185964,0.0005033882,0.003279669,0.9812362,0.00009630063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001905894,0.00003490931,0.0002651806,0.0001135844,0.00005946457,0.000117307,0.9976971,0.000269145,0.001252647],"genre_scores_gemma":[0.00134663,0.00003772824,0.0009822291,0.0001381548,0.00002615915,0.001417217,0.9925776,0.000253581,0.003220711],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1631733,"threshold_uncertainty_score":0.5458692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.229694193343023,"score_gpt":0.4736178370139285,"score_spread":0.2439236436709055,"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."}}