{"id":"W6977091556","doi":"10.60692/qr4qz-1bj45","title":"Interoperability opportunities and challenges in linking mhealth applications and eRecord systems: Botswana as an exemplar","year":2021,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"mHealth; Interoperability; eHealth; Semantic interoperability; Context (archaeology); Cross-domain interoperability; Information and Communications Technology","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":[0.00525308,0.0003851176,0.0002378284,0.001461511,0.003971998,0.004693505,0.001070749,0.001708573,0.002264621],"category_scores_gemma":[0.005264312,0.0003457484,0.0003420741,0.003472107,0.00244483,0.00346655,0.004253441,0.0014331,0.0003941807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006930658,"about_ca_system_score_gemma":0.008107895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04216864,"about_ca_topic_score_gemma":0.0683665,"domain_scores_codex":[0.9969732,0.001611106,0.0002062402,0.0001764094,0.0003848792,0.0006482519],"domain_scores_gemma":[0.9958243,0.002650313,0.000311075,0.0002840152,0.0006668241,0.0002634989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005213663,0.0005186803,0.1050698,0.0039082,0.00009697948,0.03173738,0.357768,0.00194591,0.03869674,0.09488278,0.01182713,0.353027],"study_design_scores_gemma":[0.00008093549,0.0005191231,0.08523347,0.006342784,0.0001214988,0.00861337,0.5025582,0.003184919,0.009455847,0.02113319,0.3625976,0.0001590281],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9040236,0.004057637,0.011322,0.02610292,0.0001480903,0.000563343,0.0002525387,0.0001035567,0.05342633],"genre_scores_gemma":[0.9750025,0.002347997,0.01358523,0.002566752,0.00001552876,0.0003204907,0.0002018101,0.00004819013,0.005911596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04216864,"threshold_uncertainty_score":0.08384639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1814465127642086,"score_gpt":0.2701643492417986,"score_spread":0.08871783647759005,"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."}}