{"id":"W1929602805","doi":"10.1111/j.1467-9310.2009.00579.x","title":"The integrative domain of foresight and competitive intelligence and its impact on R&amp;D management","year":2009,"lang":"en","type":"article","venue":"R and D Management","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Futures studies; Agile software development; Competitive advantage; Competitive intelligence; Knowledge management; Context (archaeology); Set (abstract data type); Work (physics); Process management; Business; Management science; Engineering; Computer science; Management; Marketing; Economics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003294591,0.000249295,0.0002209649,0.0002054199,0.0002681076,0.0002047411,0.0001826802,0.00002908573,0.00004116655],"category_scores_gemma":[0.00001709664,0.0001525015,0.00005598853,0.0002601132,0.0001439834,0.0002446014,0.0002719218,0.0000970632,0.0000389478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002285603,"about_ca_system_score_gemma":0.000002701036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000204667,"about_ca_topic_score_gemma":0.00008135863,"domain_scores_codex":[0.9989324,0.00001893309,0.0002565641,0.0003423352,0.0001937344,0.0002560061],"domain_scores_gemma":[0.9994482,0.000115412,0.000123925,0.0001890562,0.00009750059,0.00002589068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001440189,0.00007038208,0.0003665794,0.0001321655,0.00008656686,0.00001212518,0.00018126,0.000008454481,0.00001788268,0.9174789,0.0005254185,0.08097624],"study_design_scores_gemma":[0.001210951,0.0006372612,0.1830029,0.001523973,0.0003426697,0.00001147078,0.01117705,0.002233433,0.0008330979,0.4760113,0.321918,0.001097918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2758255,0.005862738,0.01298546,0.002848487,0.0003166501,0.002278738,0.00001160799,0.0001073942,0.6997634],"genre_scores_gemma":[0.9938643,0.003909003,0.0002885652,0.0005258675,0.00009333391,0.00002288333,0.000005084257,0.000009759829,0.0012812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7180388,"threshold_uncertainty_score":0.6218832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01778103771793546,"score_gpt":0.2776349429153244,"score_spread":0.259853905197389,"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."}}