{"id":"W4399533052","doi":"10.51161/geneticon2024/35781","title":"HEMOGLOBINOPATIAS ESTRUTURAIS: AVANÇOS E PERSPECTIVAS NA COMPREENSÃO DESSAS ANOMALIAS MOLECULARES","year":2024,"lang":"pt","type":"article","venue":"","topic":"Neonatal Health and Biochemistry","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002704189,0.0006891537,0.0006907277,0.000197955,0.00022197,0.0001874852,0.0003444798,0.0005086361,0.003874466],"category_scores_gemma":[0.0001442588,0.0005756846,0.0003988031,0.0006236261,0.0002723581,0.000151025,0.000208639,0.001003527,0.001803805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004879078,"about_ca_system_score_gemma":0.001094982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008785843,"about_ca_topic_score_gemma":0.00004193437,"domain_scores_codex":[0.996067,0.00009460698,0.0007157843,0.001204279,0.0008061364,0.001112167],"domain_scores_gemma":[0.9976361,0.0001983345,0.00008690874,0.000828067,0.0002259223,0.001024613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003878419,0.002881089,0.02865339,0.06697766,0.003520993,0.04091197,0.01091963,0.00001498318,0.3156956,0.01477009,0.3462672,0.1655089],"study_design_scores_gemma":[0.00867134,0.004325048,0.01948552,0.01586764,0.002403503,0.00971456,0.02474539,0.03631156,0.7718569,0.0005844584,0.1013319,0.004702208],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7548336,0.1501427,0.001760934,0.007119464,0.004228304,0.001820869,0.0004086706,0.001320909,0.07836445],"genre_scores_gemma":[0.9531507,0.0003907891,0.0005630053,0.001624841,0.001166555,0.00003293444,0.0001789404,0.0001061443,0.04278612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4561612,"threshold_uncertainty_score":0.9996694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0179464374605301,"score_gpt":0.3055828119157878,"score_spread":0.2876363744552577,"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."}}