{"id":"W7112086934","doi":"","title":"Special Report - From Start-up to Scale-up: A Report on the Innovation Clinic in Canada","year":2019,"lang":"","type":"article","venue":"eYLS (Yale Law School)","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commercialization; Intellectual property; Work (physics); Exploit; Experiential learning; Production (economics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002588473,0.000650138,0.0004467885,0.00305149,0.01178198,0.007375454,0.002796806,0.002970381,0.01350226],"category_scores_gemma":[0.006028043,0.0006604522,0.0009631688,0.004693305,0.001735887,0.001578885,0.003344981,0.003896581,0.001570516],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06725387,"about_ca_system_score_gemma":0.2775685,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9825196,"about_ca_topic_score_gemma":0.9932535,"domain_scores_codex":[0.9893864,0.0002926915,0.000304322,0.0004497896,0.006410606,0.003156219],"domain_scores_gemma":[0.9791868,0.001090374,0.0006819568,0.0002443997,0.009837675,0.00895883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000349782,0.001223202,0.2030828,0.001255779,0.0001310227,0.008034856,0.01405834,0.000647658,0.004899649,0.008955485,0.5829828,0.1743785],"study_design_scores_gemma":[0.00005383748,0.0003517528,0.3035633,0.0005669783,0.0001143872,0.001827832,0.04189069,0.0005815757,0.00202434,0.0003271454,0.6485253,0.0001728233],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5076557,0.02434601,0.003289588,0.1801074,0.008521263,0.003968637,0.04996749,0.001108631,0.2210352],"genre_scores_gemma":[0.6637126,0.02751545,0.004239346,0.05135164,0.001061889,0.0009288912,0.02009384,0.0006406877,0.2304556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9327461,"threshold_uncertainty_score":0.4879633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0471198597927758,"score_gpt":0.3208996871905365,"score_spread":0.2737798273977606,"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."}}