{"id":"W3139258132","doi":"10.1002/arp.1815","title":"Integrated geophysical study in the cemetery of Marquis of Haihun","year":2021,"lang":"en","type":"article","venue":"Archaeological Prospection","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Ministry of Natural Resources","keywords":"Ground-penetrating radar; Excavation; Geophysical survey; Geology; Magnetic anomaly; Geophysics; Magnetic survey; Anomaly (physics); Electrical resistivity tomography; Archaeology; Interpretation (philosophy); Exploration geophysics; Radar; Remote sensing; Paleontology; Geography; Electrical resistivity and conductivity; Engineering; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001729131,0.00007143911,0.0001802095,0.00002792597,0.00001851817,0.000002771496,0.0001045501,0.00003624564,0.00002549617],"category_scores_gemma":[0.0000833274,0.00004635375,0.00005639469,0.0005295487,0.0001102111,0.00002621905,0.00004595213,0.000189716,0.00000407131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001241417,"about_ca_system_score_gemma":0.000004965756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000824135,"about_ca_topic_score_gemma":0.0000401181,"domain_scores_codex":[0.9993121,0.0001162065,0.0002218822,0.0001292718,0.0001176359,0.0001029116],"domain_scores_gemma":[0.9995518,0.0001709257,0.00002712615,0.0001874735,0.00004715529,0.00001548055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00009057413,0.005338826,0.2186307,0.0001741576,0.0001359603,0.00004394298,0.006857704,0.002598793,0.6082661,0.0906577,0.00008918577,0.06711631],"study_design_scores_gemma":[0.0002295495,0.0002878963,0.9311455,0.000009228777,0.00001336951,0.000003238801,0.0008649599,0.001572863,0.01760884,0.04809577,0.00009875379,0.00006995667],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945961,0.00002690749,0.004270078,0.0001321093,0.00004628107,0.0002497565,0.000003240086,0.00003618587,0.0006393841],"genre_scores_gemma":[0.9960708,0.000008582208,0.003775257,0.00001427112,0.00002886783,0.0000752067,0.000003957174,0.000004734311,0.00001830409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7125149,"threshold_uncertainty_score":0.1890251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0380981116204585,"score_gpt":0.2672385327528247,"score_spread":0.2291404211323662,"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."}}