{"id":"W4393089305","doi":"10.5267/j.dsl.2024.3.001","title":"Factors affecting the decision of selection the green growth: The case of business firms and its accountancy policy","year":2024,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Business and Economic Development","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Business; Accounting; Industrial organization; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001770487,0.0001255808,0.0001236534,0.0001257776,0.0006164687,0.0001830896,0.0006064268,0.00002911918,0.0001150494],"category_scores_gemma":[0.0004288864,0.00005188363,0.00004212492,0.002401097,0.0006339136,0.0006295844,0.000435588,0.0001165443,0.00002161749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001315399,"about_ca_system_score_gemma":0.00004460516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001971915,"about_ca_topic_score_gemma":0.0002731081,"domain_scores_codex":[0.9986873,0.00003047279,0.0002949562,0.0003401092,0.0004142768,0.0002329011],"domain_scores_gemma":[0.9986163,0.000951455,0.0001163213,0.0002425897,0.00003413254,0.00003914212],"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":[0.00005129802,0.00005031984,0.0794827,0.00005237514,0.00002918887,0.00005400438,0.01711282,0.005726202,0.09420348,0.0009322863,0.004431066,0.7978743],"study_design_scores_gemma":[0.0001177697,0.00001542741,0.9800389,0.00009766572,0.00001218621,0.000299684,0.0009605827,0.01000735,0.005849811,0.001419849,0.001030458,0.0001503473],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990554,0.00006757228,0.002658098,0.006005461,0.000402763,0.0002021304,0.000003073758,0.00001089949,0.00009605204],"genre_scores_gemma":[0.9992241,0.00003200298,0.0001513303,0.0005198283,0.00004266034,0.000004737327,1.876401e-7,0.000007248691,0.0000179608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9005561,"threshold_uncertainty_score":0.4741442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207837274735791,"score_gpt":0.2640951616887229,"score_spread":0.242016788941365,"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."}}