{"id":"W7028211370","doi":"","title":"Ep 83 - Tech for Tanks w/ Curtis Kolibab","year":2023,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Product (mathematics); High tech; Sustainability; Agriculture; Internet of Things; Order (exchange)","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":["insufficient_payload"],"category_scores_codex":[0.0006907952,0.0007906529,0.0003200922,0.000927343,0.004180501,0.005009654,0.0006923319,0.00183183,0.6040819],"category_scores_gemma":[0.00247208,0.0005110737,0.0002950803,0.0007334335,0.0005807121,0.002474905,0.0029066,0.002752308,0.3775581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002625756,"about_ca_system_score_gemma":0.003482286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03102454,"about_ca_topic_score_gemma":0.09932697,"domain_scores_codex":[0.9989333,0.00006678481,0.00002852884,0.0002228049,0.0004940862,0.0002545504],"domain_scores_gemma":[0.9984768,0.0001384411,0.00007689332,0.0001124922,0.0006821284,0.0005132292],"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":[0.00001805371,0.000009558545,0.00007106421,0.00004295719,6.989976e-7,0.0001045215,0.0001141079,0.00001213626,0.000263641,0.001101786,0.9773344,0.02092708],"study_design_scores_gemma":[0.000001049227,0.00000379891,0.0001902435,0.00002461566,3.535532e-7,0.00004116117,0.000125685,0.000008450198,0.00006374498,0.00006002621,0.9994782,0.000002657617],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00140166,0.004664631,0.0007782619,0.02150066,0.009807301,0.0001457118,0.001695763,0.001358392,0.9586477],"genre_scores_gemma":[0.0009236032,0.0004065544,0.0001045076,0.0008538659,0.0001257277,0.000009609876,0.0001355958,0.0001565892,0.9972838],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3959181,"threshold_uncertainty_score":0.5647292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01540076114939119,"score_gpt":0.1799321452514636,"score_spread":0.1645313841020725,"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."}}