{"id":"W4386607606","doi":"10.17261/pressacademia.2023.1753","title":"INVESTIGATING VALUE CREATION AND COMPETITIVE ADVANTAGE OF DIGITAL ECOSYSTEMS: NEXT-GENERATION COLLABORATION AND BIG DATA ENVIRONMENTS","year":2023,"lang":"en","type":"article","venue":"Pressacademia","topic":"Digitalization and Economic Development in Agriculture","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Digital ecosystem; Big data; Competitive advantage; Ecosystem; Digital transformation; Value (mathematics); Analytics; Computer science; Sustainable Value; Business; Data science; Knowledge management; Ecology; Sustainability; Marketing; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.0002103098,0.0001055427,0.0001265571,0.0001023509,0.00009371468,0.0004648064,0.0001123183,0.00007838187,0.000009811586],"category_scores_gemma":[0.0001375944,0.00009860675,0.000007054849,0.0002255588,0.00004620407,0.003352876,0.0002788225,0.000056395,0.00002676307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001477584,"about_ca_system_score_gemma":0.00001088073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008358714,"about_ca_topic_score_gemma":0.00001280881,"domain_scores_codex":[0.9992212,0.000008163037,0.0002776925,0.0002631072,0.0001261808,0.0001036234],"domain_scores_gemma":[0.9995757,0.00003318803,0.0002381348,0.0001115808,0.00002589181,0.00001548756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002306729,0.0000889674,0.691494,0.001148855,0.0001905624,0.000003595218,0.001461165,0.001544757,0.02537718,0.194083,0.03744629,0.04713861],"study_design_scores_gemma":[0.001801713,0.00001819778,0.07511503,0.0004004813,0.0001351265,0.000005418437,0.007537062,0.3085872,0.001390402,0.005880802,0.5982573,0.000871272],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9763239,0.000143105,0.0004356611,0.0006705465,0.0003460459,0.0004611741,0.0001771373,0.0001086492,0.0213338],"genre_scores_gemma":[0.9950402,0.0001352539,0.00007705913,0.0002000989,0.0003821241,0.00001300485,0.003642303,0.00001189681,0.0004979917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.616379,"threshold_uncertainty_score":0.4482139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0670089048183477,"score_gpt":0.247294998078151,"score_spread":0.1802860932598033,"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."}}