{"id":"W4410875374","doi":"10.5267/j.dsl.2025.4.002","title":"The strategized business model for successful technopreneurs in Malaysian Small-Medium Enter-prise (SME) using Business Intelligence (BI) as a moderator , Pages:649-660","year":2025,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Moderation; Small and medium-sized enterprises; Business intelligence; Business; Knowledge management; Process management; 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":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002232383,0.0005597488,0.0005206949,0.001672314,0.001374851,0.003111312,0.003771372,0.0001604124,0.00003089335],"category_scores_gemma":[0.002030356,0.0004217548,0.0001359291,0.009809808,0.001189278,0.003777735,0.001154854,0.0003855267,0.00005203584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001992032,"about_ca_system_score_gemma":0.000531318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006726136,"about_ca_topic_score_gemma":0.0005486911,"domain_scores_codex":[0.9951624,0.00002117487,0.001076778,0.001416434,0.001134031,0.001189183],"domain_scores_gemma":[0.9964493,0.0004515835,0.000446175,0.001304377,0.001292767,0.00005580173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001893954,0.0006343574,0.01669086,0.00077052,0.00005869394,0.0001520004,0.0002415432,0.5400774,0.1516034,0.02957868,0.004585936,0.2537127],"study_design_scores_gemma":[0.0005939569,0.000005846988,0.003898676,0.0006952714,0.00005350512,0.000009707246,0.0004972462,0.9627895,0.00413614,0.02393989,0.002724742,0.0006555123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4854465,0.00006637038,0.504213,0.008022483,0.001208583,0.0007256871,0.000008267708,0.00009575953,0.0002133183],"genre_scores_gemma":[0.9881923,0.000107896,0.005073007,0.006019119,0.0002727846,0.0001623069,0.00001909252,0.00004715082,0.0001063739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5027458,"threshold_uncertainty_score":0.9999252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07584559880996261,"score_gpt":0.3286126737808919,"score_spread":0.2527670749709293,"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."}}