{"id":"W6968506907","doi":"10.5281/zenodo.14864945","title":"Testing of eCREAM interface modules","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASTER","funders":"European Commission","keywords":"Interface (matter); Interoperability; User interface; Software; Data extraction; Software development","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":[0.00955786,0.001199987,0.0006776504,0.001012753,0.0004099938,0.001867617,0.003281779,0.001469441,0.01524496],"category_scores_gemma":[0.03380248,0.0007500655,0.0007951084,0.0005783172,0.0008140687,0.004003294,0.003534623,0.001323159,0.00558128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017675,"about_ca_system_score_gemma":0.001472848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001249587,"about_ca_topic_score_gemma":0.000550167,"domain_scores_codex":[0.9875457,0.002876899,0.001575116,0.001611969,0.005366305,0.00102393],"domain_scores_gemma":[0.9795628,0.006489944,0.000831095,0.005601921,0.007062101,0.0004522215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005585681,0.00260409,0.03242327,0.003032454,0.0003218808,0.002503408,0.007836125,0.0171783,0.2380365,0.02524711,0.0654548,0.5997764],"study_design_scores_gemma":[0.0006168392,0.003531226,0.02623833,0.0005240156,0.0001685525,0.002040795,0.0008006012,0.07334389,0.702437,0.001995996,0.1881095,0.0001932102],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5312862,0.0005676295,0.3601847,0.0008315565,0.0007166978,0.003963765,0.006590549,0.06525137,0.03060753],"genre_scores_gemma":[0.6297249,0.0003450987,0.3063275,0.001408635,0.0001145245,0.003158651,0.01609496,0.01133824,0.03148743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01524496,"threshold_uncertainty_score":0.05099946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1147542930372243,"score_gpt":0.3951002331822315,"score_spread":0.2803459401450072,"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."}}