{"id":"W2971048662","doi":"10.18653/v1/d19-1403","title":"Induction Networks for Few-Shot Text Classification","year":2019,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":201,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Ping (video games); Natural language processing; Shot (pellet); Artificial intelligence; Joint (building); Computer security; Engineering; Chemistry","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":[0.001559228,0.001653233,0.00223042,0.003653061,0.001597407,0.001483748,0.003738035,0.002567396,0.006905869],"category_scores_gemma":[0.006119912,0.001011058,0.001742171,0.002794941,0.0007458083,0.004159567,0.002076177,0.003441118,0.005772803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00157783,"about_ca_system_score_gemma":0.001255786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009542249,"about_ca_topic_score_gemma":0.01487319,"domain_scores_codex":[0.9985119,0.0003506923,0.0001038901,0.00059672,0.0002501072,0.0001867247],"domain_scores_gemma":[0.9964752,0.00201962,0.0002457125,0.0005298071,0.0005769248,0.0001527876],"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":[0.0005899864,0.0004230716,0.002955102,0.0005088663,0.000314734,0.000302176,0.0002165686,0.1364349,0.005549151,0.01432617,0.04124043,0.7971388],"study_design_scores_gemma":[0.00001132725,0.00002770539,0.0003492705,0.00002092454,0.00003460806,0.00004252357,0.00002132232,0.973224,0.001150924,0.02312657,0.001979467,0.00001142738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02110923,0.004640156,0.9558504,0.001036968,0.0005380843,0.0002363934,0.002812232,0.01015346,0.003623114],"genre_scores_gemma":[0.5254271,0.002800598,0.4142004,0.001055535,0.001339198,0.001181945,0.02397471,0.00125588,0.02876454],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009542249,"threshold_uncertainty_score":0.02310246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07470951185655068,"score_gpt":0.2798845743633619,"score_spread":0.2051750625068112,"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."}}