{"id":"W2885861159","doi":"10.5267/j.msl.2018.7.007","title":"Implementation of business intelligence framework for Malaysian halal food manufacturing industry towards initiate strategic financial performance management","year":2018,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Teknikal Malaysia Melaka","keywords":"Business; Business intelligence; Process management; Food industry; Marketing; Knowledge management; Industrial organization; Computer science; Food 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"],"consensus_categories":[],"category_scores_codex":[0.000935896,0.0003914478,0.0002949632,0.001006743,0.000641532,0.0005985719,0.001631543,0.0001254711,0.0003660007],"category_scores_gemma":[0.00002600801,0.0003801598,0.0000861359,0.002425084,0.0008490711,0.002792671,0.0008500963,0.0002545962,0.0001045802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001041638,"about_ca_system_score_gemma":0.00002995172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001696649,"about_ca_topic_score_gemma":0.00004205796,"domain_scores_codex":[0.9966214,0.000008582673,0.0006580755,0.0008851271,0.0009021954,0.0009246535],"domain_scores_gemma":[0.9985796,0.00001933687,0.0004860104,0.0006614969,0.0002156645,0.00003784125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002894991,0.000321556,0.02976641,0.005194849,0.0001945748,0.00003573774,0.0003082619,0.001631793,0.001380537,0.5402522,0.001749986,0.4188746],"study_design_scores_gemma":[0.001542807,0.000317403,0.7902813,0.001738261,0.0005576839,0.00001102154,0.006149491,0.006916332,0.09471609,0.08055299,0.01460454,0.002612074],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7946151,0.000007252042,0.1957746,0.001633059,0.001474445,0.001017122,0.00001540182,0.0001086365,0.005354323],"genre_scores_gemma":[0.9859287,0.00002346014,0.009396456,0.003453868,0.0009440459,0.0001443253,0.0000348394,0.0000324114,0.00004196114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7605149,"threshold_uncertainty_score":0.9998651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07586245243749638,"score_gpt":0.3140557390944508,"score_spread":0.2381932866569544,"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."}}