{"id":"W7114920771","doi":"10.5194/ica-abs-10-126-2025","title":"Interoperable Global and Local Indexing of Discrete Global Grid Systems Based on the ISEA Projection for Efficient Storage, Processing and Transmission","year":2025,"lang":"en","type":"article","venue":"Abstracts of the ICA","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Resources Canada","keywords":"Projection (relational algebra); Search engine indexing; Transmission (telecommunications); Interoperability; Grid; Key (lock)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005100796,0.0001039805,0.0001588329,0.00002025315,0.0001892517,0.0001221277,0.0003831316,0.00004976363,1.260371e-7],"category_scores_gemma":[0.00004269235,0.00005717606,0.00004623288,0.0002538643,0.00008850204,0.00006002537,0.00008071333,0.00007477437,9.449905e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005280829,"about_ca_system_score_gemma":0.0001217885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002191456,"about_ca_topic_score_gemma":0.00000510228,"domain_scores_codex":[0.9990823,0.00008053707,0.0002765733,0.0002164515,0.0002005289,0.0001436132],"domain_scores_gemma":[0.9993598,0.0001150538,0.0001781093,0.0002294978,0.00008615492,0.00003139637],"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":[0.0003241437,0.0002698589,0.001970835,0.002197825,0.00006914818,0.000001929027,0.0005686825,0.9054446,0.0006299415,0.01116923,0.001161624,0.07619216],"study_design_scores_gemma":[0.0003717065,0.0001059938,0.008662881,0.001424302,0.00001584543,0.000005588666,0.000107114,0.9876551,0.0005677947,0.0001806197,0.0008318372,0.00007122688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1927274,0.0003772705,0.803449,0.001062297,0.000446743,0.0005916228,0.00002965486,0.00003051838,0.001285491],"genre_scores_gemma":[0.9994908,0.0000010361,0.0004113942,0.00004384945,0.00001858827,0.000008335734,0.000001234595,0.000002239161,0.00002251907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8067634,"threshold_uncertainty_score":0.2331572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009979243912898273,"score_gpt":0.2537276073764801,"score_spread":0.2437483634635819,"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."}}