{"id":"W3083845092","doi":"10.48550/arxiv.2009.04806","title":"SketchEmbedNet: Learning Novel Concepts by Imitating Drawings","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sketch; Computer science; Principle of compositionality; Salient; Generative grammar; Artificial intelligence; Focus (optics); Class (philosophy); Natural (archaeology); Natural language processing; Algorithm","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":[0.0005373494,0.001656746,0.0006730722,0.0009868963,0.0002462871,0.00117412,0.002344389,0.001458358,0.01076525],"category_scores_gemma":[0.003057467,0.0006442045,0.0009779106,0.0008770324,0.0006907169,0.003110512,0.001446952,0.001609358,0.002442898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007152389,"about_ca_system_score_gemma":0.0004372248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001668769,"about_ca_topic_score_gemma":0.004709794,"domain_scores_codex":[0.9996731,0.00005713232,0.0000110581,0.0001680633,0.0000679402,0.00002272855],"domain_scores_gemma":[0.9995339,0.000179808,0.00003718575,0.0001639667,0.00004544225,0.00003972417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003686084,0.0002711536,0.002226142,0.000743343,0.0002610234,0.0004659507,0.0002538924,0.2019196,0.02307662,0.03081025,0.04543312,0.6941702],"study_design_scores_gemma":[0.00004672545,0.0001008247,0.000376697,0.0000384583,0.0000278883,0.000233012,0.00004862818,0.9564621,0.007808426,0.02205977,0.01277666,0.00002080326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05114506,0.00123038,0.9212096,0.0004706343,0.0003842257,0.0003103451,0.002997668,0.01387132,0.008380767],"genre_scores_gemma":[0.3625559,0.001189195,0.6097357,0.0004495155,0.0001269042,0.0005489976,0.009407943,0.001140884,0.01484502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01076525,"threshold_uncertainty_score":0.03601336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06690291441134907,"score_gpt":0.2260820636634177,"score_spread":0.1591791492520686,"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."}}