{"id":"W2571250672","doi":"10.17266/35.2.6","title":"The \"Madre Sana\" Data Set","year":2016,"lang":"en","type":"article","venue":"Connections","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences","keywords":"Data set; Set (abstract data type); Geography; Cartography; 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":[0.002021026,0.0008773809,0.001449414,0.004933725,0.0008317064,0.001885257,0.002336752,0.001963666,0.02942637],"category_scores_gemma":[0.01767646,0.0006042972,0.001489747,0.009078562,0.0004124569,0.0009345685,0.002184551,0.001630699,0.01198419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087326,"about_ca_system_score_gemma":0.003759494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06971955,"about_ca_topic_score_gemma":0.111611,"domain_scores_codex":[0.9979546,0.0005379037,0.0003327841,0.0003420245,0.0005595842,0.0002730459],"domain_scores_gemma":[0.9925904,0.002525662,0.001312731,0.001738639,0.001192909,0.0006396124],"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":[0.0005801985,0.000136165,0.02922103,0.0009459059,0.0004852224,0.0001000368,0.0001556846,0.001599509,0.0001774937,0.002003019,0.953666,0.01092978],"study_design_scores_gemma":[0.001229125,0.0001044102,0.1220009,0.001361665,0.0004403218,0.0003547109,0.0009484237,0.002206959,0.0006700795,0.002794681,0.8677791,0.0001096393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003840293,0.000141514,0.0001259405,0.000347776,0.00003909109,0.00003639106,0.9933913,0.0001305315,0.001947333],"genre_scores_gemma":[0.01113421,0.0001691832,0.0005125675,0.0002333283,0.00004047229,0.000340465,0.9856219,0.00006463069,0.001883319],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06971955,"threshold_uncertainty_score":0.1386275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1393264977433903,"score_gpt":0.4149461931511724,"score_spread":0.2756196954077821,"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."}}