{"id":"W4414882172","doi":"10.1111/jfpe.70221","title":"Advances in Soft Sensors for Smart Food Drying: Innovations, Challenges, and Industrial Perspectives","year":2025,"lang":"en","type":"article","venue":"Journal of Food Process Engineering","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Robustness (evolution); Soft sensor; Key (lock); Quality (philosophy); Product (mathematics); Process (computing); Process control; Food products","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":[0.0022336,0.0006654841,0.0008024452,0.001048238,0.0002838855,0.001587115,0.0006383537,0.001513702,0.002661666],"category_scores_gemma":[0.001323249,0.0003517306,0.0006177883,0.001126128,0.0007957371,0.002954235,0.001009897,0.002341182,0.000891356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005117313,"about_ca_system_score_gemma":0.0009170862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004347497,"about_ca_topic_score_gemma":0.0006750003,"domain_scores_codex":[0.9993868,0.0001452311,0.00003777879,0.00009291511,0.0002680408,0.00006924332],"domain_scores_gemma":[0.9987502,0.0006660934,0.0001081354,0.00004391708,0.0003608249,0.00007081063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001931829,0.000236916,0.001018635,0.01855066,0.0001233996,0.0006177763,0.0003728879,0.004993188,0.06592982,0.08422634,0.02122149,0.8025157],"study_design_scores_gemma":[0.00002776682,0.000814396,0.001871718,0.003737404,0.0001514755,0.001430366,0.0006796692,0.008297701,0.03472017,0.04653099,0.9016232,0.000115153],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00464187,0.9740335,0.01001591,0.004659612,0.0008095059,0.00001662606,0.00003608095,0.00004957711,0.005737381],"genre_scores_gemma":[0.04043054,0.9457082,0.008249875,0.001557924,0.001167899,0.00003259284,0.00005387916,0.00001447092,0.002784752],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002661666,"threshold_uncertainty_score":0.01181251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02118153173785042,"score_gpt":0.2515861644977931,"score_spread":0.2304046327599427,"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."}}