{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"92f21ff3e31e","filters":{"venue":"언어과학"}},"results":[{"id":"W3214027216","doi":"","title":"독자변인을 적용한 영어와 국어 읽기능력 진단체계의 독서지수 상관관계 분석","year":2021,"lang":"ko","type":"article","venue":"언어과학","topic":"Educational Systems and Policies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Reading (process); Test (biology); Psychology; Mathematics education; Quarter (Canadian coin); Linguistics","authors":[{"name":"우길주","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02807878334198681,"gpt":0.2899200419469318,"spread":0.2618412586049449,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003167308,0.000241052,0.0003033597,0.00008078437,0.0003220244,0.0005590663,0.0007713892,0.0001453331,0.0009061548],"category_scores_gemma":[0.0001120333,0.0002385457,0.0001728296,0.0007007694,0.00008149774,0.0003313164,0.0003638887,0.0002347048,0.002771061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009962151,"about_ca_system_score_gemma":0.0008534195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001487645,"about_ca_topic_score_gemma":0.0002213932,"domain_scores_codex":[0.9978243,0.0001811954,0.0004194671,0.0005494718,0.0004970145,0.0005285853],"domain_scores_gemma":[0.998182,0.0002134196,0.0001533633,0.0009187706,0.0002883863,0.0002440665],"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":[0.00000384078,0.0005012231,0.01858879,0.0002046008,0.0001508195,0.0001362417,0.03078145,0.0001133268,0.002304089,0.5641651,0.3667921,0.01625854],"study_design_scores_gemma":[0.0002602996,0.00006763333,0.07637338,0.0002147043,0.00002446206,0.0001733425,0.0008130905,0.000899543,0.002857697,0.004404846,0.9134201,0.0004908962],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6544251,0.02295065,0.009245642,0.1021135,0.02688695,0.0006191579,0.0001443535,0.0003554844,0.1832592],"genre_scores_gemma":[0.8979442,0.0002138962,0.002248933,0.003539718,0.002830423,0.00002381497,0.00002200312,0.00002509928,0.09315192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5597602,"threshold_uncertainty_score":0.9980054,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3183792165","doi":"","title":"Error Patterns and Interference Features of French-Speaking Learners of KSL/KFL","year":2007,"lang":"en","type":"article","venue":"언어과학","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Linguistics; Pronunciation; Vocabulary; Spelling; Computer science; First language; Artificial intelligence; Word order; Suffix; Language transfer; Natural language processing; Verb; Contrastive analysis; Politeness; Error analysis; Second-language acquisition; Second language; Psychology; Comprehension approach; Natural language; Mathematics","authors":[{"name":"Seong-Sook Yim","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03975713725728201,"gpt":0.2753190900037494,"spread":0.2355619527464674,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003144715,0.00008055146,0.0001437503,0.00007903868,0.00007953894,0.00002930926,0.0000906815,0.00003339474,0.0004417065],"category_scores_gemma":[0.00005199915,0.00006567015,0.00003472398,0.00001480775,0.0001298639,0.00006927326,0.00003707539,0.0002340315,0.000004208639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006422431,"about_ca_system_score_gemma":0.000006932587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002667539,"about_ca_topic_score_gemma":0.002883393,"domain_scores_codex":[0.9994435,0.00003475925,0.0001730798,0.0001130926,0.0000979757,0.000137558],"domain_scores_gemma":[0.9996214,0.00009852555,0.0001165535,0.0001028019,0.0000311491,0.00002960723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00005745246,0.0001275369,0.09183032,0.0004115702,0.0001086594,0.00001695789,0.6772395,0.00003056027,0.003272839,0.08756369,0.001375281,0.1379656],"study_design_scores_gemma":[0.001767734,0.00142665,0.5180107,0.002342199,0.0001693545,0.00003341209,0.2469905,0.0002229501,0.009958084,0.001888918,0.216004,0.001185446],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9314933,0.0002627313,0.0001977309,0.00005747126,0.0001534049,0.00003320918,0.000006753228,0.00002585959,0.06776958],"genre_scores_gemma":[0.9962102,0.000008236838,0.0000901676,0.00005062547,0.0001352675,4.071096e-7,0.000004434126,0.000009186057,0.003491475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.430249,"threshold_uncertainty_score":0.4836376,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}