{"id":"W1918467556","doi":"10.5539/mas.v9n12p77","title":"Social Integration of Disabled People in Russia Using Virtual Computer Technologies","year":2015,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Educational Innovations and Challenges","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Disabled people; Life span; Psychology; Renting; Literacy; Social integration; Quality of life (healthcare); Quality (philosophy); Process (computing); Gerontology; Computer science; Sociology; Applied psychology; Political science; Pedagogy; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003638864,0.0001581969,0.0002820378,0.0009344933,0.002080049,0.001244578,0.0002158004,0.0003352846,0.002731328],"category_scores_gemma":[0.0009875331,0.0001068734,0.0002348428,0.0006124498,0.0007106365,0.0006157825,0.00181543,0.0004225661,0.0001854297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008094172,"about_ca_system_score_gemma":0.0008386004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01575366,"about_ca_topic_score_gemma":0.01454124,"domain_scores_codex":[0.99945,0.0002047461,0.00003194354,0.00003794033,0.0001011272,0.0001741676],"domain_scores_gemma":[0.9996519,0.00006035174,0.00009922867,0.00001098137,0.00003769451,0.0001398577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001567949,0.000771068,0.7747896,0.0002364395,0.00005014056,0.00264762,0.1408247,0.0001907667,0.002609236,0.001867007,0.001412909,0.07444371],"study_design_scores_gemma":[0.000009337418,0.0003056515,0.7888768,0.0001588391,0.00003857182,0.001261537,0.2000837,0.0003200018,0.0003239209,0.0004268248,0.00817245,0.00002235091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975578,0.0002294593,0.00003177824,0.0001565746,0.000007111278,0.000007334042,0.00001669991,0.000001945438,0.001991306],"genre_scores_gemma":[0.9990469,0.0003306816,0.0000197564,0.00003103142,0.000003827444,0.000006607777,0.00001836872,7.616861e-7,0.000542125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01575366,"threshold_uncertainty_score":0.03132391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08461956910269147,"score_gpt":0.3227528403040383,"score_spread":0.2381332712013468,"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."}}