{"id":"W4387438388","doi":"10.2139/ssrn.4427295","title":"Designing Airdrops","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Aerospace Engineering and Energy Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Political science; Computer science; Business","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007677911,0.0001276032,0.0001237993,0.0001323514,0.00009990257,0.00003694473,0.0001478015,0.00006306998,0.000007903264],"category_scores_gemma":[0.00001724298,0.0001226276,0.0000662137,0.0003592994,0.000008489699,0.0001013424,0.00001095748,0.0009746117,0.0003024089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003203802,"about_ca_system_score_gemma":0.0001353822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009244261,"about_ca_topic_score_gemma":0.0000404444,"domain_scores_codex":[0.9977098,0.00001592075,0.0001522617,0.00008629203,0.0001488197,0.001886872],"domain_scores_gemma":[0.9997599,0.00002251348,0.00001615599,0.0001109047,0.00001607627,0.00007451219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003092153,0.000004002908,0.0004629699,0.00001882649,0.0001942862,0.00001935885,0.0002391444,0.9577119,0.008951608,0.01826083,0.004274957,0.009859027],"study_design_scores_gemma":[0.004193875,0.0009197795,0.003394176,0.0005479282,0.0001854238,0.006599803,0.02551774,0.7025117,0.0149737,0.1170819,0.1198951,0.004178963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4609292,0.005647269,0.5181993,0.0002345787,0.002854196,0.0001023796,0.000001460796,0.004141764,0.00788989],"genre_scores_gemma":[0.9938109,0.002139706,0.0001330006,0.000004966832,0.0004421165,0.00000577203,0.000002060013,0.00006226669,0.003399238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5328817,"threshold_uncertainty_score":0.5000609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005567354704116062,"score_gpt":0.1848463391191845,"score_spread":0.1792789844150684,"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."}}