{"id":"W7084114565","doi":"10.1016/j.inffus.2025.103755","title":"Modality-aligned anchor learning based on multi-level fusion for accurate scene graph generation","year":2025,"lang":"en","type":"article","venue":"Information Fusion","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Construct (python library); Scene graph; Predicate (mathematical logic); Graph; Representation (politics); Context (archaeology); Encoding (memory); Redundancy (engineering); Scalability; Discriminative model","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":[0.0005216421,0.0001261347,0.0001416936,0.0002938234,0.0005455853,0.0001205393,0.0001134592,0.0001166321,0.0002884683],"category_scores_gemma":[0.0002655322,0.0000965418,0.0001002647,0.0003739849,0.00001629826,0.000433591,0.00001001457,0.00008895613,0.0001299128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007750139,"about_ca_system_score_gemma":0.00003719276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003842995,"about_ca_topic_score_gemma":0.0002395092,"domain_scores_codex":[0.9989937,0.00007631786,0.0003670342,0.000157508,0.0002146993,0.0001907611],"domain_scores_gemma":[0.999391,0.00009599877,0.0001465194,0.0001331465,0.0001746645,0.00005862252],"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":[0.00006802395,0.00001526656,0.004813474,0.0000212104,0.000004820268,1.157506e-7,0.00006256636,0.7904488,0.0001558076,0.00004253401,0.0003154001,0.2040519],"study_design_scores_gemma":[0.0006579965,0.0001247174,0.03138718,0.00003262928,0.00001625166,1.365066e-7,0.00006290888,0.9634569,0.0003529192,0.0001689913,0.00362352,0.0001158582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2751795,0.00003032925,0.7210255,0.00130899,0.0003492417,0.000330877,0.00007914758,0.0001113776,0.00158505],"genre_scores_gemma":[0.9885352,0.00002512785,0.007369371,0.001360938,0.00005152289,0.000007316085,0.00236239,0.000001279621,0.0002868031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7136561,"threshold_uncertainty_score":0.4196256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05432567268474722,"score_gpt":0.2663794274475298,"score_spread":0.2120537547627826,"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."}}