{"meta":{"query_hash":"d6ceca0547b8","filters":{"venue":"Journal of Advanced Statistics"},"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/d6ceca0547b8","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Advanced+Statistics"},"results":[{"id":"W2277372542","doi":"10.22606/jas.2017.21007","title":"Maximum L<sub><i>q</i></sub>-likelihood Estimation for Gamma Distributions","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Statistics","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Royal University; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Mathematics; Statistics; Sample size determination; Maximum likelihood; Principle of maximum entropy; Estimation theory; Robustness (evolution); Monte Carlo method; Applied mathematics","score_opus":0.01240735886334455,"score_gpt":0.28384357936913157,"score_spread":0.27143622050578703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2277372542","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020869211,0.0006939636,0.9956449,0.00016190064,0.000020209103,0.000021283904,0.00004123801,0.0002398009,0.0010897374],"genre_scores_gemma":[0.33731133,0.0043992805,0.64968294,0.00053834845,0.0004235931,0.00042746085,0.0006914528,0.0006728104,0.005852811],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99723154,0.0013524495,0.00009080839,0.00036791814,0.0008485663,0.00010867025],"domain_scores_gemma":[0.9858839,0.01202326,0.00043073992,0.00093951204,0.00064387027,0.000078733465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037966515,0.0012559975,0.0013079447,0.0009208596,0.00042403996,0.0015054094,0.0016567176,0.0013534372,0.005604232],"category_scores_gemma":[0.028824825,0.00057654554,0.0008406258,0.0016848585,0.00174651,0.0031588809,0.0018103893,0.0024824822,0.0026442797],"study_design_candidate":"theoretical_or_conceptual","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":[0.00023315358,0.000089090325,0.0033679348,0.00056781835,0.000108379536,0.00031563177,0.00029729615,0.4209321,0.0065466566,0.14321427,0.007813513,0.41651413],"study_design_scores_gemma":[0.000017374956,0.00004179407,0.0008755841,0.00006336841,0.000017612976,0.00021348572,0.000026230597,0.8933765,0.002831743,0.09777871,0.0047154664,0.00004212556],"about_ca_topic_score_codex":0.0020263398,"about_ca_topic_score_gemma":0.0014164614,"teacher_disagreement_score":0.005604232,"about_ca_system_score_codex":0.001167945,"about_ca_system_score_gemma":0.0012325869,"threshold_uncertainty_score":0.020078838},"labels":[],"label_agreement":null}]}