{"id":"W4292842654","doi":"10.3102/1431912","title":"Designing Safe Learning Environments for Discovery, Empathy, Failure, and Igniting Impact in Latin America","year":2019,"lang":"en","type":"article","venue":"Proceedings of the 2019 AERA Annual Meeting","topic":"E-Learning and Knowledge Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Latin Americans; Empathy; Computer science; Data science; Psychology; Political science; Social psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.001033921,0.0002086062,0.0002930589,0.0001404595,0.0001934011,0.0002411572,0.0006306915,0.00005542354,0.000002453983],"category_scores_gemma":[0.0004793445,0.0001617006,0.0001015087,0.0003082161,0.00006550144,0.0009172891,0.0008142629,0.0002893024,0.00001361399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006671994,"about_ca_system_score_gemma":0.00001861257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007101254,"about_ca_topic_score_gemma":0.000001915641,"domain_scores_codex":[0.9984433,0.00003611977,0.0003551851,0.000454418,0.000269788,0.0004411883],"domain_scores_gemma":[0.9990693,0.0002555378,0.0004327285,0.0001249535,0.00006497819,0.00005253822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001110311,0.0001884352,0.7689543,0.0006199579,0.000147667,0.000001548306,0.04044366,0.008600885,0.1274247,0.00428646,0.001315935,0.04790541],"study_design_scores_gemma":[0.01001023,0.004593221,0.2973901,0.009009136,0.000244937,0.00004957942,0.116276,0.3931147,0.1428836,0.005843361,0.01614832,0.004436844],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899532,0.0001395458,0.00480108,0.0003699111,0.0001142687,0.0005590161,0.000003375869,0.00004636322,0.004013211],"genre_scores_gemma":[0.9774723,0.00001314466,0.02095663,0.00004335129,0.00005245219,0.00001810845,0.000001132152,0.00002315444,0.001419743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4715642,"threshold_uncertainty_score":0.6593961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006780518463677357,"score_gpt":0.2233147938996417,"score_spread":0.2165342754359643,"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."}}