{"id":"W3015234797","doi":"10.36227/techrxiv.12100692.v1","title":"Deep Learning for text in limted data settings","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Sequence (biology); Transfer of learning; Sequence learning; Natural language processing; Machine learning; Recurrent neural network; Sentiment analysis; 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":[0.002402293,0.001139123,0.0008336513,0.001213297,0.000579152,0.00210474,0.001880608,0.002359767,0.01123751],"category_scores_gemma":[0.0100676,0.000612641,0.0007771679,0.001642792,0.0009104633,0.005339557,0.002412102,0.00391023,0.004486676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001692884,"about_ca_system_score_gemma":0.001048118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005268578,"about_ca_topic_score_gemma":0.009025916,"domain_scores_codex":[0.9988223,0.0004470582,0.00008738157,0.0002933294,0.0002385821,0.0001112877],"domain_scores_gemma":[0.9972805,0.00164856,0.0001699138,0.0004443333,0.0003651631,0.00009153636],"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":[0.0003561153,0.0003139369,0.002425988,0.0009290323,0.0001896463,0.0005135229,0.0002317176,0.2714677,0.004538766,0.1238744,0.05348805,0.5416712],"study_design_scores_gemma":[0.00001433949,0.00003006788,0.0003075212,0.00004453247,0.000008001712,0.0000466553,0.00002872829,0.8908821,0.001152188,0.09999152,0.00748411,0.00001032168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01023357,0.002729762,0.9730117,0.003458356,0.000314984,0.0001259094,0.002297839,0.002832845,0.00499507],"genre_scores_gemma":[0.4108973,0.006216614,0.5476781,0.00144195,0.0009396673,0.0007786045,0.009045492,0.0008122268,0.02218994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01123751,"threshold_uncertainty_score":0.03759319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05509319530841789,"score_gpt":0.3401015580858983,"score_spread":0.2850083627774804,"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."}}