{"id":"W4214918905","doi":"10.1088/2058-8585/ac5a39","title":"Machine learning based data driven inkjet printed electronics: jetting prediction for novel inks","year":2022,"lang":"en","type":"article","venue":"Flexible and Printed Electronics","topic":"Nanomaterials and Printing Technologies","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mean squared error; Drop (telecommunication); Computer science; Machine learning; Inkwell; Artificial intelligence; Simulation; Engineering; Mathematics; Mechanical engineering; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005111809,0.0006557429,0.0005698207,0.0006248067,0.0002058741,0.0009219328,0.0006862725,0.0008090706,0.001564664],"category_scores_gemma":[0.001735837,0.0002767731,0.0006333976,0.0008053949,0.0002411052,0.0004874602,0.0002768681,0.001009215,0.0004962939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005498651,"about_ca_system_score_gemma":0.0004104598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004385184,"about_ca_topic_score_gemma":0.002966023,"domain_scores_codex":[0.9997842,0.00003047256,0.00001747424,0.00007003854,0.00007643732,0.00002143761],"domain_scores_gemma":[0.9986708,0.0008398214,0.0001226185,0.00009531781,0.0002404425,0.00003097451],"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":[0.0001384604,0.0001299631,0.003045119,0.0001272881,0.00003009965,0.0001037881,0.00002137518,0.919076,0.007441154,0.0003063846,0.0008582691,0.06872202],"study_design_scores_gemma":[0.000001536645,0.00001577838,0.000343871,0.000003284788,0.000002134539,0.000005090471,0.000002741872,0.9964575,0.002925522,0.0001251147,0.0001143747,0.000002965004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5376942,0.001389914,0.4501486,0.0005772357,0.0001810027,0.0001394776,0.00155375,0.004472826,0.003843067],"genre_scores_gemma":[0.9475737,0.0002729502,0.04913377,0.00005287588,0.0000284467,0.00008785345,0.0008400662,0.00006255414,0.001947811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004385184,"threshold_uncertainty_score":0.008719325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02299066709761419,"score_gpt":0.2407372095856626,"score_spread":0.2177465424880484,"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."}}