{"id":"W4251726153","doi":"10.26522/ti.v2i1.710","title":"Screen shot 14","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); Computer science; Materials science; 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":[0.0006135938,0.001621457,0.001245062,0.002401411,0.0009165354,0.002503482,0.001470825,0.001142441,0.7820505],"category_scores_gemma":[0.003543641,0.001154116,0.001250689,0.001968338,0.0002543321,0.001366022,0.001973999,0.0009988501,0.5572668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005513458,"about_ca_system_score_gemma":0.0008361421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006233421,"about_ca_topic_score_gemma":0.01282785,"domain_scores_codex":[0.9996184,0.0000395602,0.00002102359,0.00008335993,0.0001467558,0.00009090359],"domain_scores_gemma":[0.9985252,0.000364137,0.00005383259,0.000365435,0.0004703759,0.0002210304],"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":[0.0002367431,0.00003481108,0.0003531476,0.0001587785,0.00002082055,0.00005696244,0.00003800754,0.0001396725,0.0009370058,0.000513093,0.980846,0.01666505],"study_design_scores_gemma":[0.0004862535,0.0000624018,0.005737722,0.0002035733,0.00005526363,0.0001826859,0.00008767947,0.003194835,0.005384317,0.004602776,0.9798869,0.0001155859],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003664468,0.000300545,0.026512,0.0006467819,0.001255531,0.000489172,0.5199293,0.3042679,0.1429344],"genre_scores_gemma":[0.02249085,0.0004345813,0.04547031,0.001270508,0.0005338591,0.001376641,0.5256425,0.1697621,0.2330187],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2179495,"threshold_uncertainty_score":0.3108785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06907756777686751,"score_gpt":0.2013940170147465,"score_spread":0.1323164492378791,"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."}}