{"meta":{"query_hash":"1c315883b99f","filters":{"venue":"2013 International Conference on Electrical Information and Communication Technology (EICT)"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/1c315883b99f","api":"https://metacan.xera.ac/api/v1/cohort?venue=2013+International+Conference+on+Electrical+Information+and+Communication+Technology+%28EICT%29"},"results":[{"id":"W1985913097","doi":"10.1109/eict.2014.6777864","title":"Native Language Identification using probabilistic graphical models","year":2014,"lang":"en","type":"article","venue":"2013 International Conference on Electrical Information and Communication Technology (EICT)","topic":"Authorship Attribution and Profiling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Graphical model; Artificial intelligence; Support vector machine; Probabilistic logic; Task (project management); Feature (linguistics); Principle of maximum entropy; Point (geometry); Natural language processing; Entropy (arrow of time); Identification (biology); Naive Bayes classifier; Machine learning; Pattern recognition (psychology); Mathematics","score_opus":0.03629424243890863,"score_gpt":0.3031466464180493,"score_spread":0.2668524039791407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985913097","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04294455,0.0004631982,0.9489942,0.0010361087,0.000057642017,0.00006672666,0.00071036624,0.0028454363,0.0028817393],"genre_scores_gemma":[0.8515342,0.0004904906,0.14218408,0.00029627883,0.00010881962,0.00014355632,0.0017436465,0.00024839127,0.0032506087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974597,0.001345587,0.00008815983,0.00049919204,0.00044300323,0.00016440042],"domain_scores_gemma":[0.9898432,0.007826376,0.0008372184,0.00062158454,0.0006865606,0.000185113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00269233,0.0009261134,0.0007613821,0.0032202548,0.0005977218,0.002512467,0.0014766403,0.001359909,0.0034619558],"category_scores_gemma":[0.017800905,0.00061577844,0.0013617352,0.0017559715,0.000901857,0.0035248436,0.0014521774,0.0016218942,0.0018073089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044450327,0.0002716185,0.018172013,0.00024765485,0.0002472611,0.0004723194,0.0006542901,0.6250513,0.0029997125,0.09484446,0.012854913,0.24373998],"study_design_scores_gemma":[0.000008472148,0.000013575456,0.00063290464,0.000014981615,0.00001351446,0.00006849758,0.000022276668,0.9552936,0.00027293776,0.042838205,0.00080820255,0.000012829177],"about_ca_topic_score_codex":0.0066378894,"about_ca_topic_score_gemma":0.006084185,"teacher_disagreement_score":0.0066378894,"about_ca_system_score_codex":0.0011050365,"about_ca_system_score_gemma":0.00090303924,"threshold_uncertainty_score":0.014238536},"labels":[],"label_agreement":null}]}