{"id":"W4235706621","doi":"10.1007/978-1-4939-7131-2_100522","title":"Instant Message","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Instant; Computer science; Food science; Chemistry","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":[],"category_scores_codex":[0.0006900418,0.000807229,0.0005677844,0.001194377,0.001920966,0.00529951,0.0009408511,0.003228333,0.641824],"category_scores_gemma":[0.005348048,0.0002316339,0.0004073995,0.0006728258,0.0006807444,0.003508018,0.002878939,0.003788179,0.5242543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009595097,"about_ca_system_score_gemma":0.001121601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001531764,"about_ca_topic_score_gemma":0.005408116,"domain_scores_codex":[0.9992296,0.0001095749,0.00001736881,0.0000957508,0.0004424834,0.0001052724],"domain_scores_gemma":[0.9987001,0.0002611265,0.00005116372,0.0001067312,0.0004751671,0.0004056444],"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":[0.000006508596,0.000004777128,0.00001468806,0.00001506379,4.56043e-7,0.00001231304,0.00001589552,0.000006219934,0.00002056812,0.00193363,0.9841058,0.01386414],"study_design_scores_gemma":[0.000002317826,0.000002235277,0.0000378444,0.00002694602,4.658395e-7,0.00001028539,0.00003848819,0.000009378668,0.00001637987,0.001200021,0.9986537,0.000001989005],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0003956569,0.003662078,0.0009593075,0.05216046,0.07733694,0.00006929737,0.001610689,0.001158738,0.8626469],"genre_scores_gemma":[0.0006953749,0.0004339084,0.0001017305,0.00837641,0.003837728,0.00002011535,0.0002212228,0.0001628147,0.9861508],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.641824,"threshold_uncertainty_score":0.5108945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05932385803991525,"score_gpt":0.194123542538764,"score_spread":0.1347996844988487,"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."}}