{"id":"W6931149712","doi":"10.5281/zenodo.2637800","title":"Artificial Intelligence in Healthcare Market Forecast to 2024","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nucleofection; Gestational period; TSG101; Dysgeusia; Diafiltration; Fusible alloy; Liquation; Hyporeflexia; Emperipolesis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001106445,0.0007032808,0.0003547966,0.002129773,0.0002572732,0.001810772,0.0004666156,0.0008619065,0.01558673],"category_scores_gemma":[0.004975301,0.0002063092,0.0007450834,0.002258045,0.0001940912,0.002076259,0.0006258857,0.00131649,0.009519549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002629997,"about_ca_system_score_gemma":0.001902429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03237523,"about_ca_topic_score_gemma":0.01923913,"domain_scores_codex":[0.9993142,0.00004518963,0.0000379163,0.00007603728,0.0004232381,0.0001035022],"domain_scores_gemma":[0.9979651,0.0002838067,0.0002935779,0.00005442118,0.001273158,0.0001299575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005369434,0.0001079838,0.0352718,0.0003128921,0.0001105856,0.0003866366,0.00008608735,0.02960261,0.001071442,0.02474976,0.8014933,0.10627],"study_design_scores_gemma":[0.0001003202,0.0003074348,0.07026839,0.0003294877,0.0001381249,0.0003262428,0.0005779866,0.08659488,0.006486912,0.018771,0.8159665,0.0001326119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1821391,0.01085586,0.03205664,0.06287136,0.01248776,0.000258548,0.4564666,0.00521162,0.2376524],"genre_scores_gemma":[0.557119,0.008397789,0.009726905,0.004388842,0.002894848,0.0002474032,0.2934916,0.0008140883,0.1229195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03237523,"threshold_uncertainty_score":0.06437355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1412237492177262,"score_gpt":0.372728098115283,"score_spread":0.2315043488975568,"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."}}