{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001057591,0.0002857513,0.0003021395,0.0003660978,0.001687466,0.001839126,0.0006810981,0.0003315576,0.007731875],"category_scores_gemma":[0.005003314,0.0001288004,0.0002476193,0.0006869026,0.0008446154,0.001010922,0.003527585,0.0009310809,0.0005269503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002618345,"about_ca_system_score_gemma":0.002516832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06694674,"about_ca_topic_score_gemma":0.1228812,"domain_scores_codex":[0.9984021,0.0008977574,0.00003453947,0.0001059708,0.0001938173,0.0003659145],"domain_scores_gemma":[0.9960799,0.0008073784,0.0006550644,0.0001172267,0.0004561992,0.001884271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001022982,0.001580588,0.5798405,0.00080069,0.00009427693,0.004038305,0.05846739,0.0006040513,0.003259848,0.006208381,0.008207146,0.3358758],"study_design_scores_gemma":[0.00002586829,0.001130143,0.9013206,0.0003413655,0.00005747397,0.0007160467,0.07042614,0.000409356,0.0009267339,0.000307934,0.02431618,0.00002222371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888719,0.000433441,0.00006821682,0.0008127006,0.00001704898,0.00001675955,0.00006026219,0.00001373256,0.009705881],"genre_scores_gemma":[0.9971837,0.0004459364,0.0002290671,0.00006414326,0.000006898371,0.00002247208,0.00005391605,0.000006556385,0.00198716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06694674,"threshold_uncertainty_score":0.1331142,"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."}}