{"id":"W2272803201","doi":"","title":"Organizational and Institutional Genesis: The Emergence of High-Tech Clusters in the Life Sciences","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Argument (complex analysis); Normative; Legitimacy; High tech; Narrative; Diversity (politics); Field (mathematics); Political science; Sociology; Public relations; Law; Biology","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":["metaresearch","bibliometrics"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.0489962,0.00008556671,0.0001291014,0.008160513,0.0008229013,0.0005545705,0.002725507,0.00005945718,0.0001475235],"category_scores_gemma":[0.01639726,0.00003828366,0.00005055703,0.06882213,0.0007591849,0.0004083729,0.0002397787,0.001263477,0.00001425908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004621136,"about_ca_system_score_gemma":0.003882669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000162716,"about_ca_topic_score_gemma":0.001072551,"domain_scores_codex":[0.9930541,0.0002497897,0.0004912294,0.0002739189,0.004942952,0.0009880157],"domain_scores_gemma":[0.9966674,0.001704291,0.0002383255,0.0002549659,0.001035165,0.00009989139],"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":[0.00001978658,0.0001177536,0.2067269,0.000001921654,0.0000258513,0.000002836098,0.0004063889,0.0003937914,0.001879401,0.7618473,0.0009879736,0.02759011],"study_design_scores_gemma":[0.0004822953,0.0002442568,0.3015653,0.00000647195,0.000008980988,0.0005075526,0.007696622,0.002713344,0.0001583489,0.6855683,0.0009126721,0.0001358608],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832492,0.003765424,0.004613764,0.007375299,0.0003809815,0.0001078085,0.000003777433,0.000002633794,0.0005011157],"genre_scores_gemma":[0.9952238,0.004177871,0.0002120765,0.0001734341,0.0001274104,0.000002597052,4.879245e-7,0.000003069516,0.00007923461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09483846,"threshold_uncertainty_score":0.991888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1829871870935589,"score_gpt":0.4570893013116872,"score_spread":0.2741021142181282,"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."}}