{"id":"W7093400772","doi":"","title":"Virtual Inclusion","year":2008,"lang":"en","type":"report","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Virtual machine; Inclusion (mineral); Virtual actor; Virtual reality; Virtual world; Extension (predicate logic); Mechanism (biology); Virtual Laboratory","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":[0.005047296,0.0008915964,0.001202971,0.001998336,0.003439949,0.008934116,0.004533365,0.002049278,0.02411488],"category_scores_gemma":[0.0202204,0.000863926,0.001635763,0.00291707,0.005822347,0.02213953,0.01930142,0.003107775,0.0056232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002052803,"about_ca_system_score_gemma":0.003156634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001839628,"about_ca_topic_score_gemma":0.001227956,"domain_scores_codex":[0.9910386,0.002165194,0.0009506455,0.00165117,0.003155299,0.001038947],"domain_scores_gemma":[0.981379,0.003907087,0.0006552151,0.01058635,0.002805997,0.0006662718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001012327,0.00005230368,0.0002805932,0.0001401482,0.00001516498,0.0001176487,0.001302468,0.0009374244,0.001175357,0.9013547,0.006045998,0.08847693],"study_design_scores_gemma":[0.00005297007,0.0001462258,0.0001854898,0.0001595055,0.00007109172,0.0006081823,0.0007683699,0.009138536,0.01163924,0.6609582,0.3162029,0.00006919175],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02162892,0.000571954,0.8350073,0.002370872,0.0007365786,0.0004401016,0.0006946753,0.004539384,0.1340101],"genre_scores_gemma":[0.4999502,0.001224858,0.3598451,0.001980316,0.0004932702,0.000922246,0.002112491,0.002026136,0.1314454],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02411488,"threshold_uncertainty_score":0.08067232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02769636163414853,"score_gpt":0.2871091202894214,"score_spread":0.2594127586552729,"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."}}