{"id":"W4408503389","doi":"10.21468/scipostphys.18.3.096","title":"Generative learning of continuous data by tensor networks","year":2025,"lang":"en","type":"article","venue":"SciPost Physics","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Université de Montréal; Perimeter Institute","funders":"Canadian Institute for Advanced Research","keywords":"Generative grammar; Computer science; Tensor (intrinsic definition); Artificial intelligence; Mathematics; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002802714,0.0008289298,0.0008815331,0.001157468,0.0006484817,0.001801642,0.00182006,0.00112409,0.002399852],"category_scores_gemma":[0.01118521,0.0007595649,0.001362377,0.001353934,0.002498145,0.00402279,0.002267063,0.00285269,0.0005719332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001589183,"about_ca_system_score_gemma":0.001080628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004422955,"about_ca_topic_score_gemma":0.005763768,"domain_scores_codex":[0.9988776,0.0006019751,0.00004388981,0.0002223405,0.0001771268,0.00007696499],"domain_scores_gemma":[0.994601,0.003354443,0.0004992096,0.00101871,0.0003011543,0.0002255623],"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":[0.0000665045,0.00004160055,0.001904556,0.00009503608,0.00006538116,0.0001014531,0.0002235316,0.6501042,0.001535361,0.3134899,0.002098838,0.03027365],"study_design_scores_gemma":[0.000002742713,0.000005246687,0.00008844814,0.000006885567,0.000002416153,0.00001579828,0.000007214739,0.9253531,0.0001696502,0.07394974,0.0003925886,0.000006159146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01668587,0.0002245568,0.9806774,0.0005121424,0.00002924216,0.00002500935,0.000183287,0.0003360766,0.00132637],"genre_scores_gemma":[0.7059894,0.001057704,0.2848756,0.0004746401,0.0001873711,0.0002338307,0.001110694,0.0003923062,0.005678461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004422955,"threshold_uncertainty_score":0.01482236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04274866320332639,"score_gpt":0.344044435391464,"score_spread":0.3012957721881376,"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."}}