{"id":"W4360598407","doi":"10.15659/uzalcbs2022.12798","title":"FARKLI MLS NOKTA BULUTU YOĞUNLUKLARININ VE KOMŞULUK YÖNTEMLERİNİN KONTROLLÜ SINIFLANDIRMAYA ETKİSİ","year":2022,"lang":"tr","type":"article","venue":"","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004191115,0.0009193313,0.001343215,0.000399265,0.002415425,0.001465907,0.001890426,0.0003272788,0.2005565],"category_scores_gemma":[0.0003420049,0.0008947093,0.0004190363,0.0008548831,0.0003494635,0.0006872495,0.002239824,0.0007126515,0.009037033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005534214,"about_ca_system_score_gemma":0.000779864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002054445,"about_ca_topic_score_gemma":0.0003463928,"domain_scores_codex":[0.9912298,0.001259723,0.001892811,0.001735721,0.002087756,0.001794193],"domain_scores_gemma":[0.9965163,0.0003278296,0.0007981723,0.001497267,0.0003281254,0.0005322629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001283365,0.001977308,0.001441775,0.0002968698,0.0002993291,0.0002280941,0.006305134,0.002612039,0.7148966,0.02498134,0.2431353,0.00254281],"study_design_scores_gemma":[0.01514033,0.00403404,0.03198928,0.0002610377,0.00148997,0.0005957977,0.01583296,0.01494267,0.05125747,0.006089478,0.8524806,0.00588637],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8893734,0.001063088,0.0005354353,0.008951169,0.01860345,0.002309628,0.002839755,0.0007777173,0.07554631],"genre_scores_gemma":[0.9609588,0.0001364523,0.001142305,0.002150422,0.001148651,0.0006215181,0.000255016,0.0001565319,0.03343033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6636391,"threshold_uncertainty_score":0.9995707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03287278533726372,"score_gpt":0.2763110909445754,"score_spread":0.2434383056073117,"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."}}