{"id":"W2964529601","doi":"10.5465/ambpp.2019.15648abstract","title":"Toward an Integrative Nomological Network of Congruence: Time to Break New Ground?","year":2019,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Behavioral and Psychological Studies","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Congruence (geometry); Nomological network; Empirical research; Computer science; Psychology; Mathematics; Social psychology; Statistics; Machine learning; Structural equation modeling","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003968248,0.0002481052,0.0005121844,0.00006916937,0.00004126312,0.00001763366,0.00064669,0.0002348428,0.006156732],"category_scores_gemma":[0.00001102634,0.0001781441,0.0001049739,0.0004825215,0.0001462759,0.0001820841,0.0002799575,0.0002994303,0.0008745565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002681808,"about_ca_system_score_gemma":0.00000287286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008737526,"about_ca_topic_score_gemma":3.067667e-7,"domain_scores_codex":[0.9982164,0.00002442582,0.0004733763,0.0005729254,0.0002768668,0.0004360056],"domain_scores_gemma":[0.9994225,0.00003511958,0.0002378979,0.00009248991,0.00005389049,0.0001581293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001756554,0.001060004,0.06691851,0.000193148,0.000708178,0.00001462061,0.008278296,0.00000837806,0.002027033,0.2422358,0.4698865,0.206913],"study_design_scores_gemma":[0.001270885,0.002488201,0.8873643,0.0001904333,0.000155391,0.00001346084,0.002588807,0.000006750439,0.0002221658,0.01682413,0.08838693,0.0004884973],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8442974,0.0001647481,0.00004456497,0.003285076,0.0001623671,0.000838234,0.000005038959,0.00007669996,0.1511259],"genre_scores_gemma":[0.961621,0.00002925998,0.001582254,0.001612926,0.00015379,0.00005207356,0.000003222922,0.00001496066,0.03493053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8204458,"threshold_uncertainty_score":0.9999034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1059952368404115,"score_gpt":0.3425767443081369,"score_spread":0.2365815074677255,"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."}}