{"id":"W2005834850","doi":"10.1016/j.techfore.2011.08.017","title":"The patent paradox – New insights through decision support using compound options","year":2011,"lang":"en","type":"article","venue":"Technological Forecasting and Social Change","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Social Sciences and Humanities Research Council of Canada; Telfer School of Management, University of Ottawa; University of Ottawa; Rensselaer Polytechnic Institute","keywords":"Enforcement; Patent troll; Value (mathematics); Business; Profit (economics); Patent infringement; Patent office; Patent analysis; Economics; Industrial organization; Law and economics; Public economics; Intellectual property; Patent law; Microeconomics; Law; Computer science; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002276504,0.0001677259,0.0001756747,0.00006645571,0.001595438,0.0001652328,0.0002395215,0.0002084775,0.0001144017],"category_scores_gemma":[0.0001403881,0.00009865801,0.00007066066,0.0003042446,0.0002757792,0.0003892805,0.0003024107,0.0002471041,0.00007559637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002193517,"about_ca_system_score_gemma":0.000007777217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009237581,"about_ca_topic_score_gemma":0.0001102304,"domain_scores_codex":[0.9990185,0.00001193312,0.0002256227,0.0002352161,0.0001731514,0.000335554],"domain_scores_gemma":[0.9996211,0.00006709815,0.0001223585,0.000106502,0.00007101529,0.00001190318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004289206,0.0003107601,0.003539175,0.00009472293,0.00009185068,0.0001218956,0.009405864,0.000002492041,0.0001933016,0.3420665,0.003782693,0.6399618],"study_design_scores_gemma":[0.001594063,0.0002897807,0.005299482,0.000238884,0.0002064316,0.00007366484,0.005408875,0.0241245,0.0002400898,0.7111347,0.2501477,0.001241851],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861417,0.0004056793,0.002605656,0.0004917869,0.0003711181,0.0003797942,0.000001701871,0.0003894012,0.009213183],"genre_scores_gemma":[0.9974808,0.00007076354,0.00103319,0.0006450074,0.0006235037,0.00001700661,0.000007789122,0.00001513849,0.0001067755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.63872,"threshold_uncertainty_score":0.9997044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6418283598268141,"score_gpt":0.2865671328002427,"score_spread":0.3552612270265714,"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."}}