{"id":"W1577271473","doi":"","title":"One Laptop per Child and Uruguay's Plan Ceibal: Impact on special education","year":2010,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Inclusive Education and Diversity","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Laptop; Plan (archaeology); Psychology; Political science; Mathematics education; Geography; Computer science; Operating system; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003605493,0.0001542694,0.0002240512,0.0001961039,0.001672468,0.00004327842,0.0005221092,0.000321343,0.003020166],"category_scores_gemma":[0.00007764364,0.0001587289,0.0001607604,0.0002012195,0.0003090109,0.0001882152,0.00006137779,0.0004689228,0.0001647304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001718685,"about_ca_system_score_gemma":0.0008563558,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01310059,"about_ca_topic_score_gemma":0.01659362,"domain_scores_codex":[0.9988838,0.0001504597,0.00008749279,0.000243601,0.0004269855,0.0002076279],"domain_scores_gemma":[0.9989668,0.00009374503,0.0002713758,0.0002456532,0.0002770046,0.0001454386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.002163375,0.001434381,0.005011935,0.0001948093,0.0004014975,0.000004262473,0.7086185,0.000006573916,0.003349979,0.09709087,0.1418471,0.03987666],"study_design_scores_gemma":[0.0003171456,0.00007497876,0.6232415,0.00006234623,0.0001910619,7.841718e-7,0.2486208,0.00000128772,0.00002656618,0.00102817,0.1261765,0.0002587356],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7060021,0.00007083016,0.000001343116,0.003125804,0.001661866,0.0002832355,0.00004683634,0.00002511015,0.2887829],"genre_scores_gemma":[0.9700131,0.0002878012,0.00005326276,0.0001448439,0.001929021,1.892672e-7,0.0003166315,0.000009991208,0.02724511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6182296,"threshold_uncertainty_score":0.9996272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01449384841643714,"score_gpt":0.2749157584336882,"score_spread":0.2604219100172511,"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."}}