{"id":"W3169494070","doi":"","title":"SketchEmbedNet: Learning Novel Concepts by Imitating Drawings","year":2021,"lang":"en","type":"article","venue":"International Conference on Machine Learning","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sketch; Computer science; Leverage (statistics); Generative grammar; Artificial intelligence; Domain (mathematical analysis); Generative model; Machine learning; Natural language processing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002839067,0.0002284852,0.000204464,0.0001149774,0.0003355288,0.0005480168,0.0007623041,0.00005626755,0.000512993],"category_scores_gemma":[0.001005892,0.0002387574,0.0000901877,0.000259573,0.00005030162,0.0006998215,0.0004117536,0.0009977119,0.0001312044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007878227,"about_ca_system_score_gemma":0.0001137535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003086629,"about_ca_topic_score_gemma":0.000003243976,"domain_scores_codex":[0.9979926,0.000125096,0.0003261839,0.0006373987,0.0005874122,0.0003312993],"domain_scores_gemma":[0.9987413,0.0002596183,0.000232716,0.0002221569,0.000420577,0.0001236648],"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":[0.00002443717,0.0001828336,0.00670823,0.00001491175,0.00008182764,0.0001009063,0.002678891,0.009988513,0.3197832,0.1934272,0.0006993107,0.4663098],"study_design_scores_gemma":[0.0007291732,0.00007583434,0.0002254695,0.0001637214,0.000003073521,0.00004900715,0.0005905175,0.9368193,0.009486285,0.001431336,0.05009373,0.0003325609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008562893,0.0002285785,0.9310497,0.006282917,0.0006253248,0.00006178144,0.000005551267,0.0003720306,0.05281121],"genre_scores_gemma":[0.9327151,0.00008691842,0.05732998,0.001490112,0.00009296993,0.000008163705,0.00008041009,0.00002434636,0.008171958],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9268308,"threshold_uncertainty_score":0.9736245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0286740712518305,"score_gpt":0.3398695443129484,"score_spread":0.3111954730611178,"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."}}