{"id":"W4411610715","doi":"10.60053/ter.2025.10.187-228","title":"КЪМ ЕДНА СЕНЗОРНА КРИТИКА: СЕНЗОРНИ КОРПУСИ И СЕНЗОРНИ ПЕЙЗАЖИ (НА ТИШИНА)","year":2025,"lang":"bg","type":"article","venue":"Терени","topic":"Medical, Sociocultural, and Biopolitical Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography","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":[0.00359866,0.0006575349,0.0003687983,0.00216733,0.005954794,0.0155763,0.0009174598,0.002349775,0.01752948],"category_scores_gemma":[0.007217178,0.0005082163,0.000558175,0.002346476,0.0133975,0.01015555,0.005180242,0.003820456,0.005471799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007160571,"about_ca_system_score_gemma":0.009820137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0127596,"about_ca_topic_score_gemma":0.01615145,"domain_scores_codex":[0.9950824,0.00171282,0.0002273076,0.0008143911,0.001623441,0.0005396633],"domain_scores_gemma":[0.9964576,0.001143092,0.0004142532,0.0003826626,0.00111707,0.0004852686],"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":[0.00003056757,0.00002356452,0.001596821,0.000199058,0.00001283805,0.000289855,0.01934469,0.0001948749,0.0004227757,0.9209911,0.01209772,0.04479609],"study_design_scores_gemma":[0.00002109476,0.0000362698,0.003985878,0.0006273519,0.00002964453,0.000656923,0.0195417,0.0003146753,0.0007223972,0.2429157,0.7310873,0.00006097462],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02928397,0.01345202,0.02200445,0.02537588,0.001198784,0.0001294943,0.0003094385,0.0001754001,0.9080706],"genre_scores_gemma":[0.8460765,0.0122564,0.02026994,0.003380673,0.0007404526,0.0002977763,0.0003251314,0.0003328934,0.1163202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01752948,"threshold_uncertainty_score":0.05864197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494753684727655,"score_gpt":0.3888750055063857,"score_spread":0.3739274686591091,"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."}}