{"id":"W2045458669","doi":"10.1177/0013164409355689","title":"Construct Commensurability and the Analysis of Change","year":2009,"lang":"en","type":"article","venue":"Educational and Psychological Measurement","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Commensurability (mathematics); Construct (python library); Construct validity; Perspective (graphical); Psychology; Epistemology; Computer science; Psychometrics; Developmental psychology; Mathematics; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01005533,0.00007949014,0.0003230577,0.0001940128,0.0001220834,0.00004805479,0.0002281705,0.000033267,0.0002604847],"category_scores_gemma":[0.02241536,0.00003668351,0.00008918479,0.00142975,0.0004002724,0.00004091449,0.00002686813,0.00009553167,0.000001552408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001031129,"about_ca_system_score_gemma":0.00001000538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001728125,"about_ca_topic_score_gemma":0.000003174578,"domain_scores_codex":[0.9976861,0.0006354199,0.0004436263,0.0003193592,0.0008038876,0.0001115902],"domain_scores_gemma":[0.9897334,0.009370411,0.0002076197,0.0002882774,0.0003291826,0.00007112291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001133535,0.0002381613,0.2871892,0.00000147242,0.00009594201,1.058677e-7,0.0003634036,0.000001730438,0.00004686611,0.02782203,0.001032169,0.6830955],"study_design_scores_gemma":[0.0002734202,0.00006506579,0.8152519,0.000002688109,0.00005212763,0.00000248272,0.0001037988,0.00005389929,0.000002095364,0.1835347,0.0006189644,0.00003888512],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444911,0.002050738,0.0004554794,0.04629293,0.0002804134,0.000215572,0.000008392341,0.000007006712,0.006198356],"genre_scores_gemma":[0.9960361,0.00006204933,0.002331716,0.001480299,0.00005910245,0.00001268339,9.596286e-7,6.881467e-7,0.00001641447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6830567,"threshold_uncertainty_score":0.9858193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8713064096796247,"score_gpt":0.5426906703775654,"score_spread":0.3286157393020593,"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."}}