{"id":"W4411119057","doi":"10.18653/v1/2025.repl4nlp-1","title":"Proceedings of the 10th Workshop on Representation Learning for NLP (RepL4NLP-2025)","year":2025,"lang":"en","type":"paratext","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung; European Commission; Azrieli Foundation; Open Philanthropy Project; UK Research and Innovation; National Science Foundation","keywords":"Natural language processing; Computer science; Artificial intelligence; Representation (politics); Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0122812,0.004157718,0.003637262,0.002970936,0.001442477,0.008281058,0.008022809,0.004995269,0.09328277],"category_scores_gemma":[0.02461428,0.001833967,0.003785396,0.002789591,0.002082271,0.0143672,0.009532961,0.008808618,0.05463525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003358053,"about_ca_system_score_gemma":0.004474444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009184893,"about_ca_topic_score_gemma":0.01226157,"domain_scores_codex":[0.9897893,0.004862245,0.000778568,0.002188016,0.001736726,0.0006452057],"domain_scores_gemma":[0.9862855,0.00644824,0.0002794724,0.003882837,0.002104355,0.0009995752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004838208,0.0004266938,0.0004003932,0.0009384493,0.00026047,0.0003102449,0.0003862839,0.005161555,0.002253636,0.01307924,0.710022,0.2662772],"study_design_scores_gemma":[0.0002183635,0.0002353097,0.001006854,0.0008091499,0.0001429462,0.0003851948,0.0003017346,0.05589259,0.004015812,0.05906381,0.8778355,0.00009268623],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01125683,0.03155585,0.7417165,0.03122806,0.02036811,0.001574899,0.03390015,0.07298899,0.05541063],"genre_scores_gemma":[0.04062182,0.01649203,0.5455583,0.009913193,0.004595652,0.003299029,0.2428933,0.0216421,0.1149846],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.09328277,"threshold_uncertainty_score":0.3120619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0242233933492539,"score_gpt":0.331406712129957,"score_spread":0.3071833187807032,"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."}}