{"id":"W2955789822","doi":"10.5281/zenodo.3266480","title":"Ruthwell Cross - Main","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Polygon (computer graphics); Resolution (logic); High resolution; Mathematics; Low resolution; Computer science; Artificial intelligence; Geography; Remote sensing; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006301041,0.001853074,0.001351374,0.003017225,0.001775898,0.005806508,0.002055357,0.002497237,0.9393394],"category_scores_gemma":[0.004282893,0.001623714,0.000905582,0.003070466,0.0006191611,0.005446301,0.003965699,0.002825032,0.8862599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017455,"about_ca_system_score_gemma":0.001118294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003561595,"about_ca_topic_score_gemma":0.007984541,"domain_scores_codex":[0.9991469,0.00006530723,0.00003424298,0.0003215816,0.0003521118,0.00007990606],"domain_scores_gemma":[0.9972824,0.0004754207,0.0001209893,0.0008371056,0.0007429302,0.0005411676],"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":[0.00007014612,0.0000578469,0.0001416376,0.0001731094,0.000007210648,0.0001269799,0.00007505661,0.0001904706,0.00109927,0.005386397,0.8834357,0.1092361],"study_design_scores_gemma":[0.00000922422,0.00001636012,0.0002649867,0.00006868872,0.000004946648,0.0001068919,0.000044375,0.00018508,0.0006589918,0.001208938,0.9974176,0.00001391273],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.0007713807,0.001037225,0.007385775,0.001095706,0.0009871842,0.0001005959,0.007302468,0.02061498,0.9607047],"genre_scores_gemma":[0.002177108,0.0007145304,0.001708513,0.0002472723,0.00009661102,0.00005947085,0.004278576,0.006074797,0.984643],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.0606606,"threshold_uncertainty_score":0.0865249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03479440192434198,"score_gpt":0.3117209869347539,"score_spread":0.2769265850104119,"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."}}