{"id":"W2581205609","doi":"10.5267/j.dsl.2016.12.001","title":"Investigation and evaluation of key success factors in technological innovation development based on BWM","year":2017,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Economic and Technological Developments in Russia","field":"Social Sciences","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Key (lock); Management science; Computer science; Process management; Business; Knowledge management; Engineering","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":[0.007134864,0.00008226199,0.0001228683,0.0006566001,0.0008723211,0.0001724437,0.000717937,0.0001127829,0.00003473503],"category_scores_gemma":[0.006076491,0.00006501986,0.00001007083,0.0007880527,0.002324324,0.0005168533,0.0001187988,0.0001207506,0.000005144189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003106251,"about_ca_system_score_gemma":0.0003010449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006480617,"about_ca_topic_score_gemma":0.0001036674,"domain_scores_codex":[0.9980322,0.00005892553,0.0003460781,0.0003480255,0.001009587,0.0002052293],"domain_scores_gemma":[0.9990596,0.0001948119,0.0002883019,0.0002720625,0.0001428482,0.0000423862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009927421,0.00002013901,0.7785769,0.000001584562,0.000001213212,7.646366e-7,0.000957915,0.0001098513,0.00374405,0.02597131,0.0000272915,0.1905791],"study_design_scores_gemma":[0.000274401,0.0000105545,0.9781833,0.00005327451,0.000001539777,5.53882e-8,0.0002822257,0.001324878,0.01011216,0.009335321,0.0003252326,0.00009701535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930318,0.000002293023,0.001052815,0.003390791,0.0001349219,0.0002439484,5.241717e-7,0.00002949701,0.002113424],"genre_scores_gemma":[0.9931281,0.00000256232,0.006460277,0.0003798807,0.000005017179,0.00001609131,0.000001294316,0.000002136155,0.000004616713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1996065,"threshold_uncertainty_score":0.8564068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1411698973015872,"score_gpt":0.3789955883628562,"score_spread":0.2378256910612691,"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."}}