{"id":"W2769490371","doi":"10.1016/j.jengtecman.2017.11.002","title":"Licensing speed: Its determinants and payoffs","year":2017,"lang":"en","type":"article","venue":"Journal of Engineering and Technology Management","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Commercialization; Negotiation; Business; Payment; Industrial organization; Scope (computer science); Process (computing); Appeal; Task (project management); Marketing; License; Microeconomics; Economics; Computer science; Management; Sociology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002316647,0.000117258,0.0001811584,0.0004624858,0.0002277209,0.0002452172,0.0002376099,0.00007269025,0.00001007475],"category_scores_gemma":[0.0001484985,0.00009370117,0.00002522175,0.00007848906,0.00004895098,0.0004930085,0.0003041269,0.0001778694,0.00001442308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008546559,"about_ca_system_score_gemma":0.000001997844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006549841,"about_ca_topic_score_gemma":0.000001680927,"domain_scores_codex":[0.9994097,0.000001322451,0.0002061623,0.0001115713,0.00009636069,0.0001748736],"domain_scores_gemma":[0.9994948,0.000008512232,0.000232455,0.000164389,0.00008799029,0.00001187004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002660223,0.0002887193,0.0822378,0.003434428,0.001104345,0.003014866,0.0002075171,0.0006841226,0.01384266,0.06564531,0.004834656,0.8244395],"study_design_scores_gemma":[0.008140409,0.0005655668,0.1759445,0.004670722,0.001325153,0.00152666,0.001195985,0.2430972,0.009881829,0.008620868,0.5426317,0.00239935],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939831,0.0005641796,0.0002256754,0.00115628,0.0005078416,0.00008926544,2.192191e-7,0.00004868186,0.003424708],"genre_scores_gemma":[0.9985958,0.0002776165,0.0004326953,0.00008831532,0.0002180049,6.057702e-7,1.118214e-7,0.00001306169,0.000373763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8220402,"threshold_uncertainty_score":0.3821023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04568488575427691,"score_gpt":0.2146197828317828,"score_spread":0.1689348970775059,"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."}}