{"id":"W4226204139","doi":"10.2139/ssrn.3868599","title":"InnoVAE: Generative AI for Understanding Patents and Innovation","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Generative grammar; Business; Knowledge management; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0007854372,0.0006401699,0.0006167282,0.001680326,0.0006836685,0.002556034,0.001591368,0.001643018,0.01289963],"category_scores_gemma":[0.004789652,0.000404863,0.001650274,0.001044102,0.001839237,0.003611325,0.001979981,0.002148501,0.001167184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008607436,"about_ca_system_score_gemma":0.0008117637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00286872,"about_ca_topic_score_gemma":0.003839061,"domain_scores_codex":[0.9996358,0.0001631043,0.00001455715,0.00007134582,0.00008638314,0.0000287816],"domain_scores_gemma":[0.9982719,0.001397397,0.00005114578,0.0001865492,0.00005357099,0.00003943107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003355428,0.00005470895,0.001764276,0.0002620665,0.0001195684,0.0001772012,0.0006045835,0.07035231,0.001425337,0.8489205,0.005769345,0.07051651],"study_design_scores_gemma":[0.00001439658,0.00001154034,0.0001944892,0.00003786639,0.00003101513,0.00006126366,0.00009372737,0.2787595,0.0007246452,0.7093913,0.0106694,0.00001095552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01246858,0.0005697551,0.9498511,0.001682495,0.0001618016,0.00006827128,0.0007671519,0.003421179,0.03100972],"genre_scores_gemma":[0.5611757,0.001325709,0.4219302,0.000832574,0.0002099374,0.0003861027,0.001436734,0.0008541069,0.011849],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01289963,"threshold_uncertainty_score":0.04315358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1499595182323307,"score_gpt":0.25553120987386,"score_spread":0.1055716916415293,"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."}}