{"id":"W2562143758","doi":"","title":"FINANCING INTELLECTUAL PROPERTY ASSESTS: AN EMPIRICAL ANALYSIS","year":2016,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Private Equity and Venture Capital","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intellectual property; Loan; Novelty; Intangible property; Business; Property (philosophy); Finance; Trademark; Tangible property; Intangible good; Computer science; Economics; Economy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008741152,0.0004315848,0.0004801757,0.003566432,0.001318239,0.004614574,0.001824504,0.002082552,0.02963463],"category_scores_gemma":[0.06531867,0.0003919005,0.0007117209,0.003233695,0.001985965,0.005853483,0.002405866,0.003895425,0.003662847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002807989,"about_ca_system_score_gemma":0.002745296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005884287,"about_ca_topic_score_gemma":0.004757121,"domain_scores_codex":[0.9958989,0.001854158,0.0002880195,0.0003043268,0.0008956441,0.0007589483],"domain_scores_gemma":[0.8228769,0.1403072,0.02197955,0.002867826,0.007345081,0.004623311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006754021,0.004820942,0.9345627,0.0003215402,0.0001656661,0.0007670501,0.002811623,0.002239779,0.0001871002,0.0142977,0.007057662,0.03209284],"study_design_scores_gemma":[0.0001968671,0.001680096,0.9022421,0.0005417501,0.0005105093,0.0006977333,0.04633034,0.01457145,0.001159115,0.007009125,0.02498823,0.00007280453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980643,0.0005933552,0.0007722001,0.001427252,0.00001771647,0.0003293828,0.001248854,0.00002300207,0.0149452],"genre_scores_gemma":[0.9933413,0.0004110595,0.0003180953,0.0001621909,0.00004368302,0.0001956569,0.001230237,0.000008660073,0.004289239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02963463,"threshold_uncertainty_score":0.09913772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03710923622670888,"score_gpt":0.270169397992003,"score_spread":0.2330601617652941,"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."}}