{"id":"W4376599933","doi":"10.5281/zenodo.7936819","title":"A SCIENTOMETRIC ANALYSIS OF CHRONIC WASTING DISEASE RESEARCH PRODUCTIVITY","year":2023,"lang":"en","type":"paratext","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Healthcare and Environmental Waste Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wasting; Productivity; Chronic wasting disease; Disease; Computer science; Data science; Medicine; Economics; Internal medicine; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003480558,0.000227493,0.0005567903,0.006808084,0.00158987,0.0002815482,0.0008235456,0.0001185045,0.02177143],"category_scores_gemma":[0.001911085,0.0002304731,0.0002088503,0.01657755,0.0004325706,0.0001126887,0.002743278,0.0008066196,0.04192008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00134381,"about_ca_system_score_gemma":0.00004143881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005784856,"about_ca_topic_score_gemma":0.000001096994,"domain_scores_codex":[0.9952341,0.0007371104,0.0005022638,0.0009769505,0.001784781,0.0007647348],"domain_scores_gemma":[0.9973198,0.00007595596,0.0002116589,0.00114011,0.0007238925,0.0005286353],"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":[0.0001519691,0.0006245808,0.00003926656,0.005019314,0.001165562,0.00006634938,0.0004232477,0.001178373,0.0007554147,0.00009305087,0.8332357,0.1572472],"study_design_scores_gemma":[0.0003792453,0.0005267743,0.008372823,0.0005012103,0.0005597708,0.000006838255,0.0002459281,0.001754577,0.00008763183,0.000005079435,0.9873625,0.0001976224],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08529848,0.007425679,0.001659072,0.007052366,0.001422759,0.007161807,0.004296279,0.001229905,0.8844537],"genre_scores_gemma":[0.7086018,0.006105094,0.00009161234,0.0001025277,0.00127782,8.259723e-7,0.02901161,0.004038486,0.2507703],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6336834,"threshold_uncertainty_score":0.9997099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1255327973728294,"score_gpt":0.3608380423286441,"score_spread":0.2353052449558148,"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."}}