{"id":"W4408324363","doi":"10.21307/connections-2016-062","title":"The “Madre Sana” Data Set","year":2016,"lang":"en","type":"article","venue":"Connections","topic":"Racial and Ethnic Identity Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences","keywords":"Set (abstract data type); Data set; Computer science; Artificial intelligence","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":[0.001430438,0.000508992,0.0007256258,0.002753054,0.0009264122,0.001145976,0.001750402,0.0006487889,0.01752196],"category_scores_gemma":[0.006156093,0.0003755701,0.000505426,0.005532819,0.0003637248,0.0004941673,0.001655368,0.0009483791,0.006710344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000783889,"about_ca_system_score_gemma":0.001320615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05521595,"about_ca_topic_score_gemma":0.07990973,"domain_scores_codex":[0.9988227,0.00037028,0.0001117562,0.0002742099,0.0002686886,0.0001522195],"domain_scores_gemma":[0.9963117,0.0009596135,0.0006062113,0.001101006,0.0007151264,0.0003063942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000912414,0.0004650825,0.2895456,0.001079046,0.0005406596,0.0004226071,0.001693335,0.00434227,0.001638703,0.005473874,0.660439,0.03344742],"study_design_scores_gemma":[0.0002780593,0.0001110915,0.5620922,0.0004384091,0.0001510645,0.0001738402,0.003077105,0.003482485,0.001034522,0.001514029,0.4275674,0.00007973708],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.07488289,0.0001588778,0.0005965994,0.0003827153,0.00003649741,0.0002027167,0.9187078,0.0002189427,0.004813048],"genre_scores_gemma":[0.07592799,0.00008539618,0.001996298,0.000147134,0.00003121314,0.001279376,0.9171587,0.00007108079,0.00330276],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05521595,"threshold_uncertainty_score":0.1097891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2305544517604015,"score_gpt":0.460803342153378,"score_spread":0.2302488903929765,"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."}}