{"id":"W2963935808","doi":"","title":"Focused Hierarchical RNNs for Conditional Sequence Processing","year":2018,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Topic Modeling","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; McGill University; Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Computer science; Security token; Recurrent neural network; Encoder; Sequence (biology); Generalization; Context (archaeology); Artificial intelligence; Embedding; Dependency (UML); Machine learning; Artificial neural network","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":[0.000922236,0.001228571,0.0005848149,0.000661963,0.000266342,0.0005212878,0.00161904,0.0008795128,0.004601006],"category_scores_gemma":[0.002866406,0.0005010031,0.0008293509,0.0007152587,0.000416764,0.001482569,0.0007143343,0.001764027,0.001874106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001224873,"about_ca_system_score_gemma":0.001079408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01117592,"about_ca_topic_score_gemma":0.01820088,"domain_scores_codex":[0.9995672,0.0001209377,0.000025053,0.0001629634,0.0000787142,0.00004512169],"domain_scores_gemma":[0.9991304,0.0004299489,0.00007921505,0.0001504702,0.0001777485,0.00003229265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001873951,0.0001461956,0.0009268451,0.0002783444,0.0001362709,0.0001301325,0.0001154281,0.6358603,0.0234072,0.02919445,0.01177996,0.2978374],"study_design_scores_gemma":[0.000004543281,0.00001890847,0.0001225861,0.000006273221,0.000008409192,0.00001185531,0.00000322378,0.9903507,0.002350378,0.006265882,0.0008522549,0.000004988767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0111554,0.0006944706,0.9814368,0.0001887771,0.00007385543,0.00007278694,0.0004666641,0.004050342,0.001860943],"genre_scores_gemma":[0.4234661,0.0009216548,0.561296,0.0005538213,0.00017327,0.0004054809,0.003362571,0.0006052054,0.009215845],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01117592,"threshold_uncertainty_score":0.02222174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02754741548236892,"score_gpt":0.2714953414140823,"score_spread":0.2439479259317134,"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."}}