{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003425677,0.0004854472,0.0004601085,0.002329463,0.003035573,0.01636546,0.0009959262,0.003316758,0.007802669],"category_scores_gemma":[0.006315627,0.0003331476,0.0002898758,0.00227967,0.0244301,0.009450894,0.006851641,0.002678722,0.001480854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004078643,"about_ca_system_score_gemma":0.002934906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003503234,"about_ca_topic_score_gemma":0.004222556,"domain_scores_codex":[0.996161,0.002341837,0.0001285761,0.0003704596,0.0007924122,0.0002056268],"domain_scores_gemma":[0.9953886,0.003224136,0.0003298612,0.0005427054,0.000331289,0.0001833623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003111496,0.00001382813,0.0004205085,0.0002390824,0.000005067465,0.0003292017,0.008584924,0.0003546002,0.0004358645,0.9063062,0.01482673,0.06845289],"study_design_scores_gemma":[0.00001082457,0.00001903953,0.001003784,0.0005895267,0.000008875119,0.0007095175,0.00607755,0.0008068183,0.000643649,0.4265052,0.5635996,0.00002567895],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.02558489,0.0597663,0.05115813,0.08482394,0.001931736,0.00006642651,0.0002989502,0.0007721886,0.7755974],"genre_scores_gemma":[0.7947707,0.06077883,0.02963284,0.008193345,0.002160098,0.0002021773,0.0002540553,0.0005270683,0.103481],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.01636546,"threshold_uncertainty_score":0.02959275,"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."}}