{"id":"W4415398785","doi":"10.1109/icdl63968.2025.11204348","title":"The Ungrounded Alignment Problem","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Open Text (Canada)","funders":"","keywords":"Bigram; Class (philosophy); Permutation (music); Point (geometry); Unsupervised learning; Boosting (machine learning)","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":[0.004036312,0.0011989,0.001981596,0.0007906187,0.002046907,0.003175657,0.003567347,0.005016735,0.01628338],"category_scores_gemma":[0.03279131,0.0008559778,0.001112381,0.001370212,0.00383074,0.01368879,0.005688067,0.005920732,0.004802979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009649226,"about_ca_system_score_gemma":0.001478573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001275182,"about_ca_topic_score_gemma":0.0009239172,"domain_scores_codex":[0.9896563,0.003149342,0.0006575364,0.004088005,0.00187579,0.0005730359],"domain_scores_gemma":[0.9824609,0.01199835,0.001157953,0.002848382,0.001098608,0.0004358124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009415507,0.0004317347,0.004970812,0.001195796,0.0001835457,0.001861401,0.002022035,0.04986871,0.009878699,0.3114614,0.04515639,0.5720279],"study_design_scores_gemma":[0.00009772403,0.0001751,0.0009806792,0.0001062135,0.0000387639,0.001312668,0.0006999531,0.1652794,0.007343226,0.8033074,0.02058843,0.00007053486],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04836148,0.001250989,0.9230458,0.00663125,0.000613048,0.0002015642,0.001146904,0.003120204,0.01562867],"genre_scores_gemma":[0.6540311,0.001028538,0.3115351,0.004421972,0.001058158,0.0006177363,0.004437996,0.001608689,0.0212607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01628338,"threshold_uncertainty_score":0.05447328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006292186822718558,"score_gpt":0.2273323189436896,"score_spread":0.2210401321209711,"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."}}