{"meta":{"query_hash":"44cdbbbeaa4a","filters":{"venue":"The Mind Research Repository"},"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/44cdbbbeaa4a","api":"https://metacan.xera.ac/api/v1/cohort?venue=The+Mind+Research+Repository"},"results":[{"id":"W2559617320","doi":"","title":"Models, forests and trees of York English: Was/were variation as a case study for statistical practice","year":2012,"lang":"en","type":"article","venue":"The Mind Research Repository","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":72,"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; University of Toronto","funders":"","keywords":"Multicollinearity; Variation (astronomy); Plural; Inference; Random forest; Computer science; Verb; Econometrics; Statistics; Variable (mathematics); Artificial intelligence; Natural language processing; Linguistics; Machine learning; Mathematics; Linear regression","score_opus":0.1341652799671293,"score_gpt":0.44939046323068943,"score_spread":0.31522518326356014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559617320","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":[0.17703253,0.00305153,0.7977618,0.0059266803,0.00010075989,0.00011376236,0.00093095435,0.00062761264,0.0144543825],"genre_scores_gemma":[0.8305165,0.0006038111,0.1648829,0.00016213863,0.000044874792,0.00022147378,0.00050704164,0.00027817738,0.0027831579],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9916339,0.0066496176,0.0002966412,0.0007751536,0.00044505773,0.00019968514],"domain_scores_gemma":[0.95853263,0.037692323,0.0010788583,0.0016011415,0.00077460374,0.00032036056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012831006,0.000455837,0.00082950067,0.0022599052,0.0017003485,0.004018558,0.0015527997,0.0009115392,0.0045616576],"category_scores_gemma":[0.035412118,0.00048611106,0.0009381585,0.0036192033,0.0057283915,0.004287416,0.001729113,0.0014659432,0.00033557927],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008022285,0.000028041826,0.009747171,0.00019039621,0.000056665067,0.00035310126,0.009034278,0.023648137,0.0002812197,0.91953874,0.0035188035,0.03352324],"study_design_scores_gemma":[0.000016716982,0.000024582216,0.0044465484,0.00012457323,0.000023770432,0.0002502441,0.0023176363,0.11600526,0.00024325884,0.8650813,0.011417683,0.00004839346],"about_ca_topic_score_codex":0.02266771,"about_ca_topic_score_gemma":0.03839583,"teacher_disagreement_score":0.02266771,"about_ca_system_score_codex":0.0035341813,"about_ca_system_score_gemma":0.0015160872,"threshold_uncertainty_score":0.06785762},"labels":[],"label_agreement":null}]}