{"id":"W4393284460","doi":"10.48550/arxiv.2403.17381","title":"Application-Driven Innovation in Machine Learning","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Biological Infrastructure; Office of International Science and Engineering; Abdul Latif Jameel Water and Food Systems Lab, Massachusetts Institute of Technology; Harvard Data Science Initiative, Harvard University; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research; National Science Foundation","keywords":"Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04599912,0.000695203,0.0008331029,0.002726912,0.002024268,0.01000493,0.003311217,0.004393826,0.004769511],"category_scores_gemma":[0.0621246,0.000598334,0.001124314,0.003090687,0.01623386,0.01495551,0.007570815,0.007713065,0.001833582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004374322,"about_ca_system_score_gemma":0.005161413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008625782,"about_ca_topic_score_gemma":0.0006540957,"domain_scores_codex":[0.9670938,0.02187532,0.0008793667,0.002537703,0.006780506,0.0008333525],"domain_scores_gemma":[0.8760691,0.09606232,0.00309293,0.01434714,0.008464932,0.001963545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001512339,0.00007769461,0.0008266894,0.0002447218,0.0000200782,0.00007088391,0.001055258,0.002485579,0.0003670182,0.9541177,0.002971472,0.03774786],"study_design_scores_gemma":[0.00001938541,0.0000556775,0.0003324315,0.0001766103,0.000009034959,0.0001184109,0.0003832692,0.01276878,0.001245997,0.9089005,0.07596172,0.00002811756],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02268598,0.01152471,0.747547,0.08611669,0.001775575,0.0004347802,0.0001066624,0.0007959174,0.1290126],"genre_scores_gemma":[0.6097195,0.01087923,0.3393667,0.01331344,0.003195013,0.001228451,0.0001703707,0.0004624748,0.02166488],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04599912,"threshold_uncertainty_score":0.2432695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1061853734691915,"score_gpt":0.2201274122885152,"score_spread":0.1139420388193237,"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."}}