{"meta":{"query_hash":"5f806d8889a7","filters":{"venue":"International Journal of Digital Health"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/5f806d8889a7","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Digital+Health"},"results":[{"id":"W3134332400","doi":"10.29337/ijdh.24","title":"Digital Health, Big Data and Connectivity: 5G and Beyond for Patient-Centred Care","year":2021,"lang":"en","type":"article","venue":"International Journal of Digital Health","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Big data; Digital health; Health care; Data science; Computer science; Psychology; Political science; Data mining","score_opus":0.1846319181436164,"score_gpt":0.46019321696863497,"score_spread":0.27556129882501856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134332400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6377978,0.119189225,0.0025546753,0.188722,0.021901079,0.0026677116,0.021590311,0.00013291121,0.005444298],"genre_scores_gemma":[0.99282056,0.0011021404,0.00032159954,0.0037747384,0.0012752485,0.000009442769,0.00047530164,0.000038972255,0.00018202492],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.996935,0.00015034384,0.0014169983,0.00042002223,0.00057152193,0.00050613174],"domain_scores_gemma":[0.9954697,0.0012254749,0.0008729842,0.00028855438,0.0015989662,0.0005443208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026995366,0.00019220298,0.00046712667,0.00019958038,0.00038625541,0.00026292857,0.0003503437,0.00011398192,0.000014236502],"category_scores_gemma":[0.0013652616,0.00017536434,0.000077343044,0.00012978663,0.00010223997,0.001061085,0.0004119177,0.0005669026,0.000016125028],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026116084,0.00013621719,0.031361107,0.00084038166,0.00012227487,0.000070666945,0.019985598,0.0000026318464,0.0000052590867,0.0017968898,0.007915387,0.93750244],"study_design_scores_gemma":[0.0027305663,0.0029806704,0.0025244798,0.004481377,0.000042943888,0.00103502,0.42624193,0.0015565958,0.00012396868,0.032849755,0.52472967,0.0007030187],"about_ca_topic_score_codex":0.000113636095,"about_ca_topic_score_gemma":0.0007712289,"teacher_disagreement_score":0.9367994,"about_ca_system_score_codex":0.00050113053,"about_ca_system_score_gemma":0.0032415183,"threshold_uncertainty_score":0.7151151},"labels":[],"label_agreement":null}]}