{"id":"W4304480647","doi":"10.18071/isz.75.0307","title":"Covid-19 és krónikus fájdalom: online felmérés a pandémia alatt fájdalommal élő, ellátásban nem részesülő személyek körében","year":2022,"lang":"hu","type":"article","venue":"Ideggyógyászati Szemle","topic":"Psychosomatic Disorders and Their Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Alexithymia; Depression (economics); Health literacy; Toronto Alexithymia Scale; Medicine; Mental health; Social support; Beck Depression Inventory; Psychology; Coronavirus disease 2019 (COVID-19); Affect (linguistics); Clinical psychology; Psychiatry; Anxiety; Health care; Disease; Internal medicine; Psychotherapist","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007599373,0.0004652907,0.0004404099,0.0005929775,0.0007556828,0.00182148,0.0003312812,0.0008906068,0.1763729],"category_scores_gemma":[0.002220767,0.0001527128,0.0001646435,0.000347363,0.0003651856,0.00155525,0.001826606,0.0009087138,0.05633673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003920332,"about_ca_system_score_gemma":0.000848605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052804,"about_ca_topic_score_gemma":0.001014694,"domain_scores_codex":[0.9996816,0.00009816537,0.00001937394,0.00004638685,0.0000777115,0.00007671017],"domain_scores_gemma":[0.9990556,0.000228029,0.00006024589,0.00004322163,0.000130463,0.0004824751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0006064834,0.0003699863,0.004042451,0.0007062117,0.00001617034,0.0009451284,0.0009184844,0.00009996707,0.002036655,0.001475676,0.7106232,0.2781596],"study_design_scores_gemma":[0.00003911902,0.00009284075,0.00614574,0.0004793877,0.000007452558,0.0008557497,0.0007965442,0.000106804,0.0005541182,0.0004159402,0.990489,0.00001740644],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1528623,0.09734512,0.003766057,0.07457244,0.03102037,0.000571854,0.02183312,0.003408199,0.6146206],"genre_scores_gemma":[0.2685545,0.05767899,0.005351526,0.00903105,0.008818245,0.0006120325,0.01243163,0.001324851,0.6361972],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1763729,"threshold_uncertainty_score":0.5900261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03860437115393669,"score_gpt":0.3304677309439025,"score_spread":0.2918633597899658,"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."}}