{"id":"W6991677017","doi":"","title":"How To Impress Anybody In This World","year":2021,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Legal Cases and Commentary","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Code (set theory); Exposition (narrative); Set (abstract data type); Face (sociological concept)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009287419,0.0006997225,0.0002958742,0.0008273566,0.005731252,0.006246908,0.001236458,0.005569954,0.3373443],"category_scores_gemma":[0.009023375,0.0002586088,0.0003797348,0.0005748349,0.002267445,0.006672126,0.004221371,0.005883991,0.2796664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001860447,"about_ca_system_score_gemma":0.003550075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01040072,"about_ca_topic_score_gemma":0.02409213,"domain_scores_codex":[0.9989675,0.0002605317,0.00002949637,0.0001013432,0.0004460796,0.0001949591],"domain_scores_gemma":[0.9977369,0.0004552231,0.0001086662,0.0002288274,0.0007714292,0.000698831],"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":[0.000001449406,0.000002287009,0.00001211371,0.00001512668,2.986896e-7,0.0000321301,0.00013586,0.000003519788,0.00001535074,0.003414844,0.9894627,0.006904256],"study_design_scores_gemma":[7.293676e-7,0.000001015636,0.00002533211,0.00006120917,4.02385e-7,0.00004438033,0.0003084403,0.000006046402,0.00002015421,0.0008144451,0.9987156,0.000002099374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002898274,0.005023687,0.0005961064,0.1313473,0.02352672,0.00004599051,0.0002888892,0.000453049,0.8384283],"genre_scores_gemma":[0.004884915,0.003282916,0.0004037066,0.05105637,0.004409476,0.00005558409,0.0001635338,0.000330555,0.935413],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3373443,"threshold_uncertainty_score":0.9451979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007803909923845351,"score_gpt":0.2078173533835165,"score_spread":0.2000134434596711,"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."}}