{"id":"W4244145547","doi":"10.26522/ti.v2i1.697","title":"Screen shot 1","year":2013,"lang":"en","type":"article","venue":"ti<","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shot (pellet); Polyglot; Mosaic; Computer science; Computer graphics (images); Artificial intelligence; Art; Materials science; Visual arts; Programming language; Metallurgy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005949757,0.00162223,0.001220786,0.00242893,0.0008876172,0.002389161,0.00134109,0.001152494,0.7728308],"category_scores_gemma":[0.003870694,0.001096702,0.001132011,0.001861068,0.0002224906,0.001361786,0.001794448,0.001004761,0.4873213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005084383,"about_ca_system_score_gemma":0.0008104719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006079902,"about_ca_topic_score_gemma":0.01322159,"domain_scores_codex":[0.9996654,0.00003873098,0.00001859838,0.00006952256,0.0001234079,0.00008434756],"domain_scores_gemma":[0.9982362,0.0005401479,0.00006653098,0.0003497933,0.0005426836,0.0002646557],"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":[0.0002580076,0.00003607685,0.0004106758,0.0002114037,0.00002061632,0.00005752631,0.00003945679,0.0001556422,0.0008740413,0.000458066,0.9822826,0.01519588],"study_design_scores_gemma":[0.0006329347,0.00007511315,0.007089002,0.0002486691,0.00006481825,0.000197675,0.000106468,0.003546626,0.005158483,0.00499692,0.9777517,0.0001317059],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003829655,0.0003099123,0.02048638,0.0007176561,0.00110823,0.0005392992,0.6283699,0.2334749,0.111164],"genre_scores_gemma":[0.02556056,0.0004760339,0.04642605,0.001754107,0.0006444779,0.001841423,0.5785325,0.1559689,0.1887959],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2271692,"threshold_uncertainty_score":0.3240293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0737825271798768,"score_gpt":0.2007509917847891,"score_spread":0.1269684646049123,"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."}}