{"id":"W7038724700","doi":"","title":"Inteligencia artificial generativa: Un contexto disruptivo en el acceso a la información [Generative artificial intelligence: A disruptive context for access to information]","year":2024,"lang":"en","type":"other","venue":"E-LIS Repository (University of Naples Federico II)","topic":"Endodontics and Root Canal Treatments","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"College of Pharmacy, University of Michigan; National Taiwan University; Universiti Putra Malaysia; University of Toronto; Monash University; University of New South Wales; Karolinska Institutet; Johns Hopkins University; Stanford Bio-X; University of Michigan; Harvard University","keywords":"Context (archaeology); Relation (database); Generative grammar; Field (mathematics); Information technology; Scientific field","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002302716,0.0006821859,0.0009698868,0.0007028133,0.0007340406,0.0007379382,0.001086668,0.0006445255,0.0006746972],"category_scores_gemma":[0.0001527178,0.0006883193,0.0005848195,0.0006713198,0.0002794058,0.0009529811,0.0009301696,0.00044356,0.0004725943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004541342,"about_ca_system_score_gemma":0.0003992777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001794723,"about_ca_topic_score_gemma":0.005201137,"domain_scores_codex":[0.9972807,0.0001787136,0.0007560751,0.0006758718,0.0006182555,0.0004903541],"domain_scores_gemma":[0.9977151,0.0002019295,0.0008102395,0.0005279716,0.0004354335,0.0003093278],"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":[0.002466196,0.001095441,0.0003401406,0.001407189,0.005973457,0.00114611,0.05537095,0.0001664124,0.002533574,0.04809409,0.7563776,0.1250288],"study_design_scores_gemma":[0.0009178961,0.001052209,0.000458787,0.001062771,0.00122393,0.0001441341,0.03487981,0.001369721,0.01344853,0.001732743,0.9417937,0.001915714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08381385,0.00320377,0.3174378,0.001691443,0.01280612,0.01083717,0.01083052,0.001418857,0.5579605],"genre_scores_gemma":[0.5748116,0.0002238869,0.004533439,0.0002939897,0.001479505,0.00009449038,0.0009406896,0.0004463539,0.417176],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4909978,"threshold_uncertainty_score":0.9995568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0450098986077135,"score_gpt":0.3389451034992724,"score_spread":0.2939352048915589,"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."}}