{"id":"W2900764028","doi":"10.1007/s11192-018-2959-4","title":"Capturing the economic value of triadic patents","year":2018,"lang":"en","type":"article","venue":"Scientometrics","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Value (mathematics); Patent analysis; Cover (algebra); Test (biology); European patent office; Patent application; Business; Computer science; Regional science; International trade; Data science; Political science; Sociology; Engineering; Law; Machine learning","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003286641,0.0005515064,0.00100847,0.01869934,0.0009628563,0.006068792,0.001015289,0.001250223,0.006101273],"category_scores_gemma":[0.04273304,0.0001683025,0.0005940022,0.03367323,0.001107949,0.008120222,0.002123713,0.001233893,0.001546666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001711711,"about_ca_system_score_gemma":0.001467173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003362383,"about_ca_topic_score_gemma":0.004088109,"domain_scores_codex":[0.9970522,0.0009463429,0.0001840919,0.0004031246,0.001121577,0.0002926789],"domain_scores_gemma":[0.9709764,0.01778681,0.004383617,0.002967216,0.002621228,0.001264662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005986696,0.0005308695,0.2738397,0.0006746607,0.0005741574,0.0009315656,0.0008950477,0.05383338,0.007256602,0.2979367,0.01416682,0.3487618],"study_design_scores_gemma":[0.00006836235,0.0002946349,0.2127849,0.0002197265,0.0003132856,0.0008913292,0.002162962,0.2906534,0.004825473,0.4575128,0.03013733,0.0001358112],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8810865,0.003673387,0.054157,0.002018965,0.0002741336,0.00008712491,0.004075849,0.0004102669,0.05421674],"genre_scores_gemma":[0.9912508,0.0007941114,0.005095562,0.00004557072,0.000229503,0.00002608017,0.00116139,0.00003130683,0.001365716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9813007,"threshold_uncertainty_score":0.02041084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.177109436578545,"score_gpt":0.2610980654164781,"score_spread":0.08398862883793304,"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."}}