{"id":"W4410331215","doi":"10.21203/rs.3.rs-6474467/v1","title":"Enhancing Firm Value through Technology Provider Networks: A Social Network Analysis Approach","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"","keywords":"Value (mathematics); Social network analysis; Business; Value network; Social network (sociolinguistics); Knowledge management; Industrial organization; Marketing; Computer science; Social media; World Wide Web; Business model","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002529233,0.0003626767,0.0004151181,0.003844978,0.0009703056,0.003695701,0.0007009552,0.001074134,0.004397551],"category_scores_gemma":[0.009259068,0.0002485052,0.0005544994,0.003498435,0.001458938,0.007051242,0.001135374,0.0008298288,0.0001822755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002430682,"about_ca_system_score_gemma":0.001558422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002291192,"about_ca_topic_score_gemma":0.003161514,"domain_scores_codex":[0.9987913,0.0007784303,0.0000231032,0.0001072092,0.0002196005,0.00008046655],"domain_scores_gemma":[0.988744,0.009747595,0.0006260446,0.0003057821,0.0003961238,0.0001804178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001538293,0.0003506965,0.01310069,0.0002627044,0.0002164481,0.0001652004,0.001586958,0.05416431,0.002410046,0.8257861,0.002260418,0.09954271],"study_design_scores_gemma":[0.00003065304,0.0000818089,0.007107562,0.00009471508,0.0001722491,0.00008822508,0.002272172,0.4427949,0.00219358,0.5397775,0.00535053,0.0000361948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.389311,0.001164779,0.5242913,0.006705844,0.00006535302,0.0002486996,0.0005450689,0.0001414311,0.07752665],"genre_scores_gemma":[0.9647669,0.0004658356,0.0318775,0.00005462156,0.00004362227,0.00007402302,0.00005084181,0.00001684723,0.002649779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004397551,"threshold_uncertainty_score":0.01763588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07544096202709957,"score_gpt":0.4258019829553198,"score_spread":0.3503610209282203,"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."}}