{"id":"W4406060353","doi":"10.32388/ojfxkj","title":"Review of: \"Distributional Matrix Completion via Nearest Neighbors in the Wasserstein Space\"","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Space (punctuation); Matrix completion; Matrix (chemical analysis); k-nearest neighbors algorithm; Combinatorics; Mathematics; Computer science; Artificial intelligence; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003075343,0.0003580338,0.0009236792,0.0001503655,0.0001007767,0.00007478645,0.002584537,0.000165427,0.0007918169],"category_scores_gemma":[0.0003065798,0.0002400669,0.0003759101,0.001499739,0.00008295957,0.0001628978,0.0004415703,0.0005900214,0.00009807375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009967339,"about_ca_system_score_gemma":0.0003941338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001758923,"about_ca_topic_score_gemma":0.00003227319,"domain_scores_codex":[0.9967062,0.0007721791,0.0008854666,0.0005498591,0.0007582941,0.0003279634],"domain_scores_gemma":[0.9973747,0.0005620818,0.0004399726,0.001244023,0.0003218435,0.00005742281],"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":[0.000001383204,0.00005363684,0.000001908788,0.0267663,0.00001582984,0.000008376666,0.00000687332,0.000002325992,0.00000102768,0.2234059,0.7453241,0.00441223],"study_design_scores_gemma":[0.0001242999,0.00003402038,0.00002358418,0.0444199,0.00006230685,0.00002694764,0.000003260698,0.00129143,0.000008831897,0.004551437,0.9492067,0.0002472611],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[4.78373e-7,0.4508961,0.3014277,0.2223769,0.001677264,0.001520692,0.0004495763,0.00008568143,0.02156554],"genre_scores_gemma":[0.0002170239,0.7139047,0.02771446,0.07969806,0.001041082,0.0004856584,0.008021651,0.00005061531,0.1688668],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.2737133,"threshold_uncertainty_score":0.9789645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02039606392485894,"score_gpt":0.3135993358874059,"score_spread":0.293203271962547,"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."}}