{"id":"W2912213232","doi":"10.2174/1874434601913010018","title":"m-Health in the Surgical Context: Prospecting, Review and Analysis of Mobile Applications","year":2019,"lang":"en","type":"article","venue":"The Open Nursing Journal","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trademark; Context (archaeology); Inclusion and exclusion criteria; Health care; Inclusion (mineral); Intellectual property; Exploratory research; Medicine; Identification (biology); Medical education; Alternative medicine; Computer science; Political science; Psychology; Geography; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.007525866,0.00011313,0.0007031659,0.0001443848,0.001314855,0.0000313533,0.0007545909,0.00006515997,0.0004722066],"category_scores_gemma":[0.0000488578,0.00006228154,0.00008028918,0.001354265,0.0001094701,0.00009818013,0.0000703461,0.001075449,0.00003756864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001998157,"about_ca_system_score_gemma":0.0008004474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003566035,"about_ca_topic_score_gemma":0.0002284305,"domain_scores_codex":[0.9966168,0.001319336,0.001163865,0.0002172631,0.0002146101,0.0004681105],"domain_scores_gemma":[0.9971284,0.0009076777,0.001007103,0.0006035041,0.0001585398,0.0001948074],"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":[0.0001793744,0.0008327657,0.09627344,0.002802872,0.0002561061,0.000001610504,0.01731311,0.00005371766,0.000007371485,0.1121446,0.05279218,0.7173429],"study_design_scores_gemma":[0.001904158,0.000271576,0.09585591,0.004224067,0.0007651087,0.000132931,0.01007405,0.0002909645,5.787547e-7,0.003953985,0.8823504,0.000176286],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0687031,0.3023264,0.001685941,0.431463,0.0008435862,0.1021575,0.0001960939,0.00007403264,0.0925504],"genre_scores_gemma":[0.884997,0.07290173,0.0006286788,0.02690254,0.0003177079,0.01228463,0.0000598317,0.00004126973,0.001866623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8295582,"threshold_uncertainty_score":0.9999853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04739198216445867,"score_gpt":0.4922408472256515,"score_spread":0.4448488650611929,"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."}}