{"id":"W2277372542","doi":"10.22606/jas.2017.21007","title":"Maximum L&lt;sub&gt;&lt;i&gt;q&lt;/i&gt;&lt;/sub&gt;-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,"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","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004768233,0.0005078564,0.0008303828,0.0001410101,0.001067138,0.0004140111,0.0006599972,0.00013488,0.0002024513],"category_scores_gemma":[0.001083414,0.0004854183,0.0003271506,0.0001391011,0.0001764519,0.0005820011,0.0001428308,0.000459433,0.00006357693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002272868,"about_ca_system_score_gemma":0.0002983008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003481078,"about_ca_topic_score_gemma":0.00001442488,"domain_scores_codex":[0.9965692,0.0000760555,0.001291778,0.0004406507,0.0007159793,0.0009063521],"domain_scores_gemma":[0.9950508,0.0007288496,0.001819507,0.0006791903,0.001147373,0.0005742123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002861869,0.0004182304,0.000084716,0.00008491912,0.00023449,0.00004527523,0.00007532213,0.001401835,0.03063461,0.7351898,0.01793167,0.2136129],"study_design_scores_gemma":[0.005286566,0.001176041,0.003919415,0.0003241651,0.0006704767,0.00003625691,0.00006683492,0.09190342,0.006903444,0.8193718,0.06938946,0.0009521755],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01383876,0.0001930791,0.972962,0.0004979661,0.001770725,0.0004961098,0.009555019,0.00002902547,0.0006573703],"genre_scores_gemma":[0.6882715,0.0001650014,0.309545,0.00004919066,0.001000866,0.00005619269,0.0006116471,0.00009106567,0.0002095392],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6744327,"threshold_uncertainty_score":0.9997597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240735886334455,"score_gpt":0.2838435793691316,"score_spread":0.271436220505787,"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."}}