{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00002746323,0.00005128152,0.00005120685,0.00002924794,0.00002926528,0.0002666165,0.0005948164,0.00002766355,0.1293802],"category_scores_gemma":[0.00008847405,0.00004772957,0.00002699022,0.0001888851,0.000001403215,0.0003473346,0.0002301332,0.00003976785,0.03967088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000098494,"about_ca_system_score_gemma":0.00003160703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.446035e-7,"about_ca_topic_score_gemma":7.057758e-7,"domain_scores_codex":[0.9995006,0.0000108707,0.00007571163,0.0001653008,0.0001263055,0.0001211694],"domain_scores_gemma":[0.9994829,0.00002518637,0.0000323682,0.0003733948,0.000038527,0.00004760488],"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":[3.218223e-7,0.00001426337,0.0002361731,0.00003518297,0.000002905891,0.000007077601,0.00005645091,0.0000706765,0.00002288542,0.008175391,0.9903515,0.001027153],"study_design_scores_gemma":[0.0001418703,0.00001340821,0.001912664,0.0001170463,3.867825e-7,0.000003797479,0.000003833607,0.07103971,0.0004793982,0.0002097502,0.9259588,0.0001194048],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.002448246,0.0003855599,0.02454115,0.001616985,0.001387036,0.001004765,0.6895429,0.002060215,0.2770131],"genre_scores_gemma":[0.6044796,0.000004802826,0.006573052,0.0109454,0.0003835697,0.00005121656,0.285264,0.00005912177,0.09223925],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.6020314,"threshold_uncertainty_score":0.9610769,"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."}}