{"id":"W4389895475","doi":"10.15184/aqy.2023.176","title":"Augmenting field data with archaeological imagery survey: mapping hilltop fortifications on the north coast of Peru","year":2023,"lang":"en","type":"article","venue":"Antiquity","topic":"Archaeological Research and Protection","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"American Council of Learned Societies; Vanderbilt University; National Science Foundation","keywords":"Archaeology; Geography; Geospatial analysis; Field survey; Terrain; Survey methodology; Sampling (signal processing); Satellite imagery; Aerial survey; Field (mathematics); Survey data collection; Remote sensing; Cartography; Computer science","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":[0.001726107,0.00007462986,0.0001102511,0.00006254935,0.0003408026,0.00001662179,0.0004803828,0.00003731258,0.0005193829],"category_scores_gemma":[0.001513902,0.0000389853,0.00002480986,0.0005722381,0.0002937246,0.000108957,0.0001771442,0.0002551624,0.00008006956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001365468,"about_ca_system_score_gemma":0.00004018495,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004156366,"about_ca_topic_score_gemma":0.02749192,"domain_scores_codex":[0.9987193,0.0002831524,0.0001564269,0.0002562829,0.0002927719,0.0002920356],"domain_scores_gemma":[0.9973735,0.00202297,0.00007034017,0.0004179663,0.00005131783,0.00006395412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008296487,0.000007065437,0.9529788,0.00001121167,0.00001257359,0.000008505617,0.0001387386,0.00009079547,0.00002684065,0.00005821855,0.0008646481,0.04571956],"study_design_scores_gemma":[0.00004626355,0.0002286403,0.993697,0.00001201566,0.000002246161,0.000002193663,0.0001801819,0.004193021,0.0001678995,0.0006894028,0.0007241811,0.00005691501],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927628,0.00001598479,0.003672838,0.002348056,0.00003447287,0.0002212682,0.0002727064,0.00004568316,0.0006261924],"genre_scores_gemma":[0.9986058,0.0001487293,0.0003150663,0.0001416516,0.00003471802,0.000002885334,0.0006608512,0.000001595453,0.00008864808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04566265,"threshold_uncertainty_score":0.9902538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1869138120562433,"score_gpt":0.3158565996875674,"score_spread":0.1289427876313241,"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."}}