{"id":"W7154003967","doi":"10.1145/3772318.3808982","title":"10.1145/3772318.3808982","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Affect (linguistics); MEDLINE; Component (thermodynamics)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001762612,0.002727988,0.002041164,0.002657909,0.002536634,0.00476637,0.002587241,0.004341104,0.9587627],"category_scores_gemma":[0.003387606,0.001556814,0.001221889,0.006979459,0.001311746,0.008894966,0.006049554,0.002121038,0.9743794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002126285,"about_ca_system_score_gemma":0.001158625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01586268,"about_ca_topic_score_gemma":0.01529819,"domain_scores_codex":[0.9992981,0.00005051394,0.00005917934,0.0001963223,0.0002490488,0.0001467681],"domain_scores_gemma":[0.9982217,0.0003883521,0.00006869075,0.0004700841,0.0004755332,0.000375703],"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":[0.0001663491,0.0001347672,0.0003483235,0.0003671876,0.00002343404,0.0001597587,0.00007151577,0.0002956256,0.0008576963,0.003719323,0.743465,0.250391],"study_design_scores_gemma":[0.00002396485,0.00002219824,0.000646434,0.000186833,0.00002075115,0.00009649707,0.00006857601,0.0004389446,0.0003184456,0.0007792349,0.9973718,0.00002638677],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001043437,0.002305698,0.00585768,0.000902454,0.001697823,0.0002732299,0.007009008,0.00946267,0.971448],"genre_scores_gemma":[0.0015166,0.0009737622,0.0009472183,0.0003806887,0.00008790587,0.0001092707,0.003387338,0.001116257,0.9914811],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04123729,"threshold_uncertainty_score":0.05882001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0238711132771695,"score_gpt":0.3520369502910638,"score_spread":0.3281658370138943,"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."}}