{"id":"W4393484579","doi":"10.5281/zenodo.10368421","title":"King Mountain Cairn (3M-grey) from SCENE 7.0","year":2017,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Archaeology; Geography; Cartography; Remote sensing; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004430626,0.0002588433,0.0002483319,0.0002442969,0.003711912,0.004032255,0.005519428,0.0001288953,0.00267067],"category_scores_gemma":[0.0002873263,0.0002927397,0.00009563459,0.0003826829,0.000132994,0.0004713704,0.004155022,0.0005160253,0.02023272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002041184,"about_ca_system_score_gemma":0.00001991409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004897052,"about_ca_topic_score_gemma":0.000004748901,"domain_scores_codex":[0.9976274,0.0002291275,0.0003129424,0.0008373292,0.0006193494,0.0003738113],"domain_scores_gemma":[0.99661,0.00006851622,0.000360543,0.002065049,0.0006801279,0.0002157638],"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":[0.000004811357,0.00008455288,1.947061e-7,0.00001982378,0.0000403716,0.00001242293,0.00009132594,0.00005923662,0.00006798267,0.004077536,0.9435578,0.05198394],"study_design_scores_gemma":[0.0002234225,0.00004770828,0.0001674272,0.00005077878,0.0000169776,0.00002154665,0.000007984862,0.002675263,0.00002085219,0.004708616,0.9917541,0.0003053156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004493073,0.0000925227,0.07454094,0.00131159,0.0003116431,0.0004710358,0.9144207,0.0006652892,0.008141317],"genre_scores_gemma":[0.001963166,0.00008034807,0.001786316,0.0002391864,0.0005199509,1.409999e-7,0.9945841,0.0005510686,0.000275678],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08016341,"threshold_uncertainty_score":0.9999525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04100120092843811,"score_gpt":0.2821539036827109,"score_spread":0.2411527027542728,"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."}}