{"id":"W3035966467","doi":"","title":"High Technology Royalty Survey Financial Terms: Descriptive Statistics and Analysis","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Licensee; Descriptive statistics; Payment; Lump sum; Business; Marketing; Statistics; Actuarial science; Mathematics; Finance; License; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001750425,0.0001707387,0.0002619027,0.0005540849,0.0003641392,0.0001355925,0.0001989124,0.0001167181,0.0001566392],"category_scores_gemma":[0.0004942267,0.0001351354,0.00005856947,0.0009069558,0.00008255366,0.0005857382,0.00009610289,0.001045561,0.0001291203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001919306,"about_ca_system_score_gemma":0.0001731484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001352943,"about_ca_topic_score_gemma":0.004247266,"domain_scores_codex":[0.9976634,0.00003887613,0.0002565444,0.0001611639,0.0001763229,0.001703742],"domain_scores_gemma":[0.9994411,0.00003989658,0.0001947052,0.0001099365,0.0001929646,0.00002132431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002438969,0.000164765,0.669345,0.00001975046,0.0009358773,0.000005740866,0.0001316348,0.00002908117,0.00005881317,0.2896971,0.001921181,0.03744714],"study_design_scores_gemma":[0.001784177,0.0002787267,0.5400061,0.00003611681,0.001913243,0.0001342429,0.001218225,0.002737009,0.0001033536,0.4386223,0.01207173,0.001094841],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9364492,0.001224726,0.06067649,0.0002125234,0.0005131204,0.0001203519,0.00002026046,0.0000519929,0.0007313526],"genre_scores_gemma":[0.9976887,0.0003383875,0.0001959014,0.0002708471,0.0006552648,0.000003144483,0.00004548505,0.00001754453,0.0007847623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1489251,"threshold_uncertainty_score":0.551066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03998359074111908,"score_gpt":0.2172221039424991,"score_spread":0.17723851320138,"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."}}